---
_id: '3591'
abstract:
- lang: eng
text: The controlled internalization of membrane receptors and lipids is crucial
for cells to control signaling pathways and interact with their environment. During
clathrin-mediated endocytosis, membrane constituents are transported via endocytic
vesicles into early endosomes, from which they are further distributed within
the cell. The small guanosine triphosphatase (GTPase) Rab5 is both required and
sufficient for the formation of these early endosomes and can be used to experimentally
address endocytic processes. Recent evidence shows that endocytic turnover of
E-cadherin regulates the migration of mesendodermal cells during zebrafish gastrulation
by modulating their adhesive interactions with neighboring cells. This in turn
leads to effective and synchronized movement within the embryo. In this review,
we discuss techniques to manipulate E-cadherin endocytosis by morpholino-mediated
knockdown of rab5 during zebrafish gastrulation. We describe the use of antibodies
specifically directed against zebrafish E-cadherin to detect its intracellular
localization and of in situ hybridization and primary cell culture to reveal patterns
of cell migration and adhesion, respectively
article_processing_charge: No
author:
- first_name: Florian
full_name: Ulrich, Florian
last_name: Ulrich
- first_name: Carl-Philipp J
full_name: Heisenberg, Carl-Philipp J
id: 39427864-F248-11E8-B48F-1D18A9856A87
last_name: Heisenberg
orcid: 0000-0002-0912-4566
citation:
ama: Ulrich F, Heisenberg C-PJ. Probing E-cadherin endocytosis by morpholino-mediated
Rab5 knock-down in zebrafish. Methods in Molecular Biology. 2008;440:371-387.
doi:10.1007/978-1-59745-178-9_27
apa: Ulrich, F., & Heisenberg, C.-P. J. (2008). Probing E-cadherin endocytosis
by morpholino-mediated Rab5 knock-down in zebrafish. Methods in Molecular Biology.
Springer. https://doi.org/10.1007/978-1-59745-178-9_27
chicago: Ulrich, Florian, and Carl-Philipp J Heisenberg. “Probing E-Cadherin Endocytosis
by Morpholino-Mediated Rab5 Knock-down in Zebrafish.” Methods in Molecular
Biology. Springer, 2008. https://doi.org/10.1007/978-1-59745-178-9_27.
ieee: F. Ulrich and C.-P. J. Heisenberg, “Probing E-cadherin endocytosis by morpholino-mediated
Rab5 knock-down in zebrafish.,” Methods in Molecular Biology, vol. 440.
Springer, pp. 371–387, 2008.
ista: Ulrich F, Heisenberg C-PJ. 2008. Probing E-cadherin endocytosis by morpholino-mediated
Rab5 knock-down in zebrafish. Methods in Molecular Biology. 440, 371–387.
mla: Ulrich, Florian, and Carl-Philipp J. Heisenberg. “Probing E-Cadherin Endocytosis
by Morpholino-Mediated Rab5 Knock-down in Zebrafish.” Methods in Molecular
Biology, vol. 440, Springer, 2008, pp. 371–87, doi:10.1007/978-1-59745-178-9_27.
short: F. Ulrich, C.-P.J. Heisenberg, Methods in Molecular Biology 440 (2008) 371–387.
date_created: 2018-12-11T12:04:08Z
date_published: 2008-01-01T00:00:00Z
date_updated: 2021-01-12T07:44:31Z
day: '01'
doi: 10.1007/978-1-59745-178-9_27
extern: '1'
intvolume: ' 440'
language:
- iso: eng
month: '01'
oa_version: None
page: 371 - 387
publication: Methods in Molecular Biology
publication_status: published
publisher: Springer
publist_id: '2792'
status: public
title: Probing E-cadherin endocytosis by morpholino-mediated Rab5 knock-down in zebrafish.
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 440
year: '2008'
...
---
_id: '3599'
abstract:
- lang: eng
text: In this paper, adaptive formation control and bio-inspired optimization are
jointly addressed for a cluster-based satellite wireless sensor network in which
there are multiple satellites flying in formation (MSFF) in the presence of unknown
disturbances. The full nonlinear dynamics model describing the relative positioning
of the MSFF system is used to develop an adaptive formation controller. First,
the original nonlinear system is transformed into a linear controllable system
with aperturbation term by invoking the input-output feedback linearization technique.
Second, by using the integral feedback design scheme, the adaptive formation controller
is presented for improving the steady-state performance of the MSFF system in
the presence of unknown disturbances. Third, as a currently popular bio-inspired
algorithm, PSO (particle swarm optimizer) is employed to minimize the total energy
consumption under the required quality of service by jointly optimizing the transmission
power and rate for each satellite. Simulation results are provided to demonstrate
the effectiveness of the adaptive formation controller and the PSO-based optimization
for saving the total communication energy.
author:
- first_name: Erfu
full_name: Yang, Erfu
last_name: Yang
- first_name: Ahmet
full_name: Erdogan, Ahmet T
last_name: Erdogan
- first_name: Tughrul
full_name: Arslan, Tughrul
last_name: Arslan
- first_name: Nicholas H
full_name: Nicholas Barton
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: 'Yang E, Erdogan A, Arslan T, Barton NH. Adaptive formation control and bio-inspired
optimization of a cluster-based satellite wireless sensor network . In: IEEE;
2008:432-439. doi:10.1109/AHS.2008.60'
apa: 'Yang, E., Erdogan, A., Arslan, T., & Barton, N. H. (2008). Adaptive formation
control and bio-inspired optimization of a cluster-based satellite wireless sensor
network (pp. 432–439). Presented at the AHS: NASA/ESA Conference on Adaptive
Hardware and Systems, IEEE. https://doi.org/10.1109/AHS.2008.60'
chicago: Yang, Erfu, Ahmet Erdogan, Tughrul Arslan, and Nicholas H Barton. “Adaptive
Formation Control and Bio-Inspired Optimization of a Cluster-Based Satellite Wireless
Sensor Network ,” 432–39. IEEE, 2008. https://doi.org/10.1109/AHS.2008.60.
ieee: 'E. Yang, A. Erdogan, T. Arslan, and N. H. Barton, “Adaptive formation control
and bio-inspired optimization of a cluster-based satellite wireless sensor network
,” presented at the AHS: NASA/ESA Conference on Adaptive Hardware and Systems,
2008, pp. 432–439.'
ista: 'Yang E, Erdogan A, Arslan T, Barton NH. 2008. Adaptive formation control
and bio-inspired optimization of a cluster-based satellite wireless sensor network
. AHS: NASA/ESA Conference on Adaptive Hardware and Systems, 432–439.'
mla: Yang, Erfu, et al. Adaptive Formation Control and Bio-Inspired Optimization
of a Cluster-Based Satellite Wireless Sensor Network . IEEE, 2008, pp. 432–39,
doi:10.1109/AHS.2008.60.
short: E. Yang, A. Erdogan, T. Arslan, N.H. Barton, in:, IEEE, 2008, pp. 432–439.
conference:
name: 'AHS: NASA/ESA Conference on Adaptive Hardware and Systems'
date_created: 2018-12-11T12:04:10Z
date_published: 2008-08-01T00:00:00Z
date_updated: 2021-01-12T07:44:34Z
day: '01'
doi: 10.1109/AHS.2008.60
extern: 1
month: '08'
page: 432 - 439
publication_status: published
publisher: IEEE
publist_id: '2784'
quality_controlled: 0
status: public
title: 'Adaptive formation control and bio-inspired optimization of a cluster-based
satellite wireless sensor network '
type: conference
year: '2008'
...
---
_id: '3600'
abstract:
- lang: eng
text: Scalability is one of the most important issues for optimization algorithms
used in wireless sensor networks (WSNs) since there are often many parameters
to be optimized at the same time. In this case it is very hard to ensure that
an optimization algorithm can be smoothly scaled up from a low-dimensional optimization
problem to the one with a high dimensionality. This paper addresses the scalability
issue of a novel optimization algorithm inspired by the Shifting Balance Theory
(SBT) of evolution in population genetics. Toward this end, a cluster-based WSN
is employed in this paper as a benchmark to perform a comparative study. The total
energy consumption is minimized under the required quality of service by jointly
optimizing the transmission power and rate for each sensor node. The results obtained
by the SBT-based algorithm are compared with the Metropolis algorithm (MA) and
currently popular particle swarm optimizer (PSO) to assess the scaling performance
of the three algorithms against the same WSN optimization problem.
alternative_title:
- LNCS
author:
- first_name: Erfu
full_name: Yang, Erfu
last_name: Yang
- first_name: Nicholas H
full_name: Nicholas Barton
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Tughrul
full_name: Arslan, Tughrul
last_name: Arslan
- first_name: Ahmet
full_name: Erdogan, Ahmet T
last_name: Erdogan
citation:
ama: 'Yang E, Barton NH, Arslan T, Erdogan A. Scalability of a novel shifting balance
theory-based optimization algorithm: A comparative study on a cluster-based wireless
sensor network. In: Vol 5216. Springer; 2008:249-260. doi:10.1007/978-3-540-85857-7_22'
apa: 'Yang, E., Barton, N. H., Arslan, T., & Erdogan, A. (2008). Scalability
of a novel shifting balance theory-based optimization algorithm: A comparative
study on a cluster-based wireless sensor network (Vol. 5216, pp. 249–260). Presented
at the IECS: International Conference on Evolvable Systems, Springer. https://doi.org/10.1007/978-3-540-85857-7_22'
chicago: 'Yang, Erfu, Nicholas H Barton, Tughrul Arslan, and Ahmet Erdogan. “ Scalability
of a Novel Shifting Balance Theory-Based Optimization Algorithm: A Comparative
Study on a Cluster-Based Wireless Sensor Network,” 5216:249–60. Springer, 2008.
https://doi.org/10.1007/978-3-540-85857-7_22.'
ieee: 'E. Yang, N. H. Barton, T. Arslan, and A. Erdogan, “ Scalability of a novel
shifting balance theory-based optimization algorithm: A comparative study on a
cluster-based wireless sensor network,” presented at the IECS: International Conference
on Evolvable Systems, 2008, vol. 5216, pp. 249–260.'
ista: 'Yang E, Barton NH, Arslan T, Erdogan A. 2008. Scalability of a novel shifting
balance theory-based optimization algorithm: A comparative study on a cluster-based
wireless sensor network. IECS: International Conference on Evolvable Systems,
LNCS, vol. 5216, 249–260.'
mla: 'Yang, Erfu, et al. Scalability of a Novel Shifting Balance Theory-Based
Optimization Algorithm: A Comparative Study on a Cluster-Based Wireless Sensor
Network. Vol. 5216, Springer, 2008, pp. 249–60, doi:10.1007/978-3-540-85857-7_22.'
short: E. Yang, N.H. Barton, T. Arslan, A. Erdogan, in:, Springer, 2008, pp. 249–260.
conference:
name: 'IECS: International Conference on Evolvable Systems'
date_created: 2018-12-11T12:04:10Z
date_published: 2008-09-08T00:00:00Z
date_updated: 2021-01-12T07:44:35Z
day: '08'
doi: 10.1007/978-3-540-85857-7_22
extern: 1
intvolume: ' 5216'
month: '09'
page: 249 - 260
publication_status: published
publisher: Springer
publist_id: '2783'
quality_controlled: 0
status: public
title: ' Scalability of a novel shifting balance theory-based optimization algorithm:
A comparative study on a cluster-based wireless sensor network'
type: conference
volume: 5216
year: '2008'
...
---
_id: '3605'
abstract:
- lang: eng
text: Many animals and plants show a correlation between the traits of the individuals
in the mating pair, implying assortative mating. Given the ubiquity of assortative
mating in nature, why and how it has evolved remain open questions. Here we attempt
to answer these questions in those cases where the trait under assortment is the
same in males and females. We consider the most favorable scenario for assortment
to evolve, where the same trait is under assortment and viability selection. We
find conditions for assortment to evolve using a multilocus formalism in a haploid
population. Our results show how epistasis in fitness between the loci that control
the focal trait is crucial for assortment to evolve. We then assume specific forms
of assortment in haploids and diploids and study the limiting cases of selective
and nonselective mating. We find that selection for increased assortment is weak
and that where increased assortment is costly, it does not invade.
author:
- first_name: Maria
full_name: De Cara, Maria A
last_name: De Cara
- first_name: Nicholas H
full_name: Nicholas Barton
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Mark
full_name: Kirkpatrick, Mark
last_name: Kirkpatrick
citation:
ama: De Cara M, Barton NH, Kirkpatrick M. A model for the evolution of assortative
mating. American Naturalist. 2008;171(5):580-596. doi:10.1086/587062
apa: De Cara, M., Barton, N. H., & Kirkpatrick, M. (2008). A model for the evolution
of assortative mating. American Naturalist. University of Chicago Press.
https://doi.org/10.1086/587062
chicago: De Cara, Maria, Nicholas H Barton, and Mark Kirkpatrick. “A Model for the
Evolution of Assortative Mating.” American Naturalist. University of Chicago
Press, 2008. https://doi.org/10.1086/587062.
ieee: M. De Cara, N. H. Barton, and M. Kirkpatrick, “A model for the evolution of
assortative mating,” American Naturalist, vol. 171, no. 5. University of
Chicago Press, pp. 580–596, 2008.
ista: De Cara M, Barton NH, Kirkpatrick M. 2008. A model for the evolution of assortative
mating. American Naturalist. 171(5), 580–596.
mla: De Cara, Maria, et al. “A Model for the Evolution of Assortative Mating.” American
Naturalist, vol. 171, no. 5, University of Chicago Press, 2008, pp. 580–96,
doi:10.1086/587062.
short: M. De Cara, N.H. Barton, M. Kirkpatrick, American Naturalist 171 (2008) 580–596.
date_created: 2018-12-11T12:04:12Z
date_published: 2008-05-01T00:00:00Z
date_updated: 2021-01-12T07:44:36Z
day: '01'
doi: 10.1086/587062
extern: 1
intvolume: ' 171'
issue: '5'
month: '05'
page: 580 - 596
publication: American Naturalist
publication_status: published
publisher: University of Chicago Press
publist_id: '2778'
quality_controlled: 0
status: public
title: A model for the evolution of assortative mating
type: journal_article
volume: 171
year: '2008'
...
---
_id: '3606'
abstract:
- lang: eng
text: 'Explicit formulae are given for the effects of a barrier to gene flow on
random fluctuations in allele frequency; these formulae can also be seen as generating
functions for the distribution of coalescence times. The formulae are derived
using a continuous diffusion approximation, which is accurate over all but very
small spatial scales. The continuous approximation is confirmed by comparison
with the exact solution to the stepping stone model. In both one and two spatial
dimensions, the variance of fluctuations in allele frequencies increases near
the barrier; when the barrier is very strong, the variance doubles. However, the
effect on fluctuations close to the barrier is much greater when the population
is spread over two spatial dimensions than when it occupies a linear, one-dimensional
habitat: barriers of strength comparable with the dispersal range (B≈σ) can have
an appreciable effect in two dimensions, whereas only barriers with strength comparable
with the characteristic scale (B\! \approx\! L \equals \sigma \sol \sqrt {2 \mu}\hskip2)
are significant in one dimension (μ is the rate of mutation or long-range dispersal).
Thus, in a two-dimensional population, barriers to gene flow can be detected through
their effect on the spatial pattern of genetic marker alleles.'
author:
- first_name: Nicholas H
full_name: Nicholas Barton
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Barton NH. The effect of a barrier to gene flow on patterns of geographic variation.
Genetical Research. 2008;90(1):139-149. doi:10.1017/S0016672307009081
apa: Barton, N. H. (2008). The effect of a barrier to gene flow on patterns of geographic
variation. Genetical Research. Cambridge University Press. https://doi.org/10.1017/S0016672307009081
chicago: Barton, Nicholas H. “The Effect of a Barrier to Gene Flow on Patterns of
Geographic Variation.” Genetical Research. Cambridge University Press,
2008. https://doi.org/10.1017/S0016672307009081.
ieee: N. H. Barton, “The effect of a barrier to gene flow on patterns of geographic
variation,” Genetical Research, vol. 90, no. 1. Cambridge University Press,
pp. 139–149, 2008.
ista: Barton NH. 2008. The effect of a barrier to gene flow on patterns of geographic
variation. Genetical Research. 90(1), 139–149.
mla: Barton, Nicholas H. “The Effect of a Barrier to Gene Flow on Patterns of Geographic
Variation.” Genetical Research, vol. 90, no. 1, Cambridge University Press,
2008, pp. 139–49, doi:10.1017/S0016672307009081.
short: N.H. Barton, Genetical Research 90 (2008) 139–149.
date_created: 2018-12-11T12:04:12Z
date_published: 2008-02-01T00:00:00Z
date_updated: 2021-01-12T07:44:37Z
day: '01'
doi: 10.1017/S0016672307009081
extern: 1
intvolume: ' 90'
issue: '1'
month: '02'
page: 139 - 149
publication: Genetical Research
publication_status: published
publisher: Cambridge University Press
publist_id: '2777'
quality_controlled: 0
status: public
title: The effect of a barrier to gene flow on patterns of geographic variation
type: journal_article
volume: 90
year: '2008'
...
---
_id: '3694'
abstract:
- lang: eng
text: Distributed Denial of Service (DDoS) attacks are today the most destabilizing
factor in the global internet and there is a strong need for sophisticated solutions.
We introduce a formal statistical framework and derive a Bayes optimal packet
classifier from it. Our proposed practical algorithm "Adaptive History-Based
IP Filtering" (AHIF) mitigates DDoS attacks near the victim and outperforms
existing methods by at least 32% in terms of collateral damage. Furthermore, it
adjusts to the strength of an ongoing attack and ensures availability of the attacked
server. In contrast to other adaptive solutions, firewall rulesets used to resist
an attack can be precalculated before an attack takes place. This ensures an immediate
response in a DDoS emergency. For evaluation, simulated DDoS attacks and two real-world
user traffic datasets are used.
author:
- first_name: Markus
full_name: Goldstein,Markus
last_name: Goldstein
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Matthias
full_name: Reif,Matthias
last_name: Reif
- first_name: Armin
full_name: Stahl,Armin
last_name: Stahl
- first_name: Thomas
full_name: Breuel,Thomas M
last_name: Breuel
citation:
ama: 'Goldstein M, Lampert C, Reif M, Stahl A, Breuel T. Bayes optimal DDoS mitigation
by adaptive history-based IP filtering. In: IEEE; 2008:174-179. doi:10.1109/ICN.2008.64'
apa: 'Goldstein, M., Lampert, C., Reif, M., Stahl, A., & Breuel, T. (2008).
Bayes optimal DDoS mitigation by adaptive history-based IP filtering (pp. 174–179).
Presented at the ICN: International Conference on Networking, IEEE. https://doi.org/10.1109/ICN.2008.64'
chicago: Goldstein, Markus, Christoph Lampert, Matthias Reif, Armin Stahl, and Thomas
Breuel. “Bayes Optimal DDoS Mitigation by Adaptive History-Based IP Filtering,”
174–79. IEEE, 2008. https://doi.org/10.1109/ICN.2008.64.
ieee: 'M. Goldstein, C. Lampert, M. Reif, A. Stahl, and T. Breuel, “Bayes optimal
DDoS mitigation by adaptive history-based IP filtering,” presented at the ICN:
International Conference on Networking, 2008, pp. 174–179.'
ista: 'Goldstein M, Lampert C, Reif M, Stahl A, Breuel T. 2008. Bayes optimal DDoS
mitigation by adaptive history-based IP filtering. ICN: International Conference
on Networking, 174–179.'
mla: Goldstein, Markus, et al. Bayes Optimal DDoS Mitigation by Adaptive History-Based
IP Filtering. IEEE, 2008, pp. 174–79, doi:10.1109/ICN.2008.64.
short: M. Goldstein, C. Lampert, M. Reif, A. Stahl, T. Breuel, in:, IEEE, 2008,
pp. 174–179.
conference:
name: 'ICN: International Conference on Networking'
date_created: 2018-12-11T12:04:39Z
date_published: 2008-04-13T00:00:00Z
date_updated: 2021-01-12T07:49:01Z
day: '13'
doi: 10.1109/ICN.2008.64
extern: 1
main_file_link:
- open_access: '0'
url: http://pub.ist.ac.at/~chl/papers/goldstein-icn2008.pdf
month: '04'
page: 174 - 179
publication_status: published
publisher: IEEE
publist_id: '2671'
quality_controlled: 0
status: public
title: Bayes optimal DDoS mitigation by adaptive history-based IP filtering
type: conference
year: '2008'
...
---
_id: '3698'
abstract:
- lang: eng
text: Kernel canonical correlation analysis (KCCA) is a dimensionality reduction
technique for paired data. By finding directions that maximize correlation, KCCA
learns representations that are more closely tied to the underlying semantics
of the data rather than noise. However, meaningful directions are not only those
that have high correlation to another modality, but also those that capture the
manifold structure of the data. We propose a method that is simultaneously able
to find highly correlated directions that are also located on high variance directions
along the data manifold. This is achieved by the use of semi-supervised Laplacian
regularization of KCCA. We show experimentally that Laplacian regularized training
improves class separation over KCCA with only Tikhonov regularization, while causing
no degradation in the correlation between modalities. We propose a model selection
criterion based on the Hilbert-Schmidt norm of the semi-supervised Laplacian regularized
cross-covariance operator, which we compute in closed form.
alternative_title:
- LNCS
author:
- first_name: Matthew
full_name: Blaschko,Matthew B
last_name: Blaschko
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Arthur
full_name: Gretton,Arthur
last_name: Gretton
citation:
ama: 'Blaschko M, Lampert C, Gretton A. Semi-supervised Laplacian regularization
of kernel canonical correlation analysis. In: Vol 5211. Springer; 2008:133-145.
doi:10.1007/978-3-540-87479-9_27'
apa: 'Blaschko, M., Lampert, C., & Gretton, A. (2008). Semi-supervised Laplacian
regularization of kernel canonical correlation analysis (Vol. 5211, pp. 133–145).
Presented at the ECML: European Conference on Machine Learning, Springer. https://doi.org/10.1007/978-3-540-87479-9_27'
chicago: Blaschko, Matthew, Christoph Lampert, and Arthur Gretton. “Semi-Supervised
Laplacian Regularization of Kernel Canonical Correlation Analysis,” 5211:133–45.
Springer, 2008. https://doi.org/10.1007/978-3-540-87479-9_27.
ieee: 'M. Blaschko, C. Lampert, and A. Gretton, “Semi-supervised Laplacian regularization
of kernel canonical correlation analysis,” presented at the ECML: European Conference
on Machine Learning, 2008, vol. 5211, no. Part 1, pp. 133–145.'
ista: 'Blaschko M, Lampert C, Gretton A. 2008. Semi-supervised Laplacian regularization
of kernel canonical correlation analysis. ECML: European Conference on Machine
Learning, LNCS, vol. 5211, 133–145.'
mla: Blaschko, Matthew, et al. Semi-Supervised Laplacian Regularization of Kernel
Canonical Correlation Analysis. Vol. 5211, no. Part 1, Springer, 2008, pp.
133–45, doi:10.1007/978-3-540-87479-9_27.
short: M. Blaschko, C. Lampert, A. Gretton, in:, Springer, 2008, pp. 133–145.
conference:
name: 'ECML: European Conference on Machine Learning'
date_created: 2018-12-11T12:04:41Z
date_published: 2008-10-21T00:00:00Z
date_updated: 2021-01-12T07:49:02Z
day: '21'
doi: 10.1007/978-3-540-87479-9_27
extern: 1
intvolume: ' 5211'
issue: Part 1
month: '10'
page: 133 - 145
publication_status: published
publisher: Springer
publist_id: '2662'
quality_controlled: 0
status: public
title: Semi-supervised Laplacian regularization of kernel canonical correlation analysis
type: conference
volume: 5211
year: '2008'
...
---
_id: '3700'
abstract:
- lang: eng
text: We propose a new method to partition an unlabeled dataset, called Discriminative
Context Partitioning (DCP). It is motivated by the idea of splitting the dataset
based only on how well the resulting parts can be separated from a context class
of disjoint data points. This is in contrast to typical clustering techniques
like K-means that are based on a generative model by implicitly or explicitly
searching for modes in the distribution of samples. The discriminative criterion
in DCP avoids the problems that density based methods have when the a priori assumption
of multimodality is violated, when the number of samples becomes small in relation
to the dimensionality of the feature space, or if the cluster sizes are strongly
unbalanced. We formulate DCP‘s separation
property as a large-margin criterion, and show how the resulting optimization
problem can be solved efficiently. Experiments on the MNIST and USPS datasets
of handwritten digits and on a subset of the Caltech256 dataset show that, given
a suitable context, DCP can achieve good results even in situation where density-based
clustering techniques fail.
acknowledgement: This work was funded in part by the EC project CLASS, IST 027978.
author:
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Lampert C. Partitioning of image datasets using discriminative context information.
In: IEEE; 2008:1-8. doi:10.1109/CVPR.2008.4587448'
apa: 'Lampert, C. (2008). Partitioning of image datasets using discriminative context
information (pp. 1–8). Presented at the CVPR: Computer Vision and Pattern Recognition,
IEEE. https://doi.org/10.1109/CVPR.2008.4587448'
chicago: Lampert, Christoph. “Partitioning of Image Datasets Using Discriminative
Context Information,” 1–8. IEEE, 2008. https://doi.org/10.1109/CVPR.2008.4587448.
ieee: 'C. Lampert, “Partitioning of image datasets using discriminative context
information,” presented at the CVPR: Computer Vision and Pattern Recognition,
2008, pp. 1–8.'
ista: 'Lampert C. 2008. Partitioning of image datasets using discriminative context
information. CVPR: Computer Vision and Pattern Recognition, 1–8.'
mla: Lampert, Christoph. Partitioning of Image Datasets Using Discriminative
Context Information. IEEE, 2008, pp. 1–8, doi:10.1109/CVPR.2008.4587448.
short: C. Lampert, in:, IEEE, 2008, pp. 1–8.
conference:
name: 'CVPR: Computer Vision and Pattern Recognition'
date_created: 2018-12-11T12:04:41Z
date_published: 2008-09-18T00:00:00Z
date_updated: 2021-01-12T07:51:35Z
day: '18'
doi: 10.1109/CVPR.2008.4587448
extern: 1
main_file_link:
- open_access: '0'
url: http://pub.ist.ac.at/~chl/papers/lampert-cvpr2008b.pdf
month: '09'
page: 1 - 8
publication_status: published
publisher: IEEE
publist_id: '2657'
quality_controlled: 0
status: public
title: Partitioning of image datasets using discriminative context information
type: conference
year: '2008'
...
---
_id: '3705'
abstract:
- lang: eng
text: 'Sliding window classifiers are among the most successful and widely applied
techniques for object localization. However, training is typically done in a way
that is not specific to the localization task. First a binary classifier is trained
using a sample of positive and negative examples, and this classifier is subsequently
applied to multiple regions within test images. We propose instead to treat object
localization in a principled way by posing it as a problem of predicting structured
data: we model the problem not as binary classification, but as the prediction
of the bounding box of objects located in images. The use of a joint-kernel framework
allows us to formulate the training procedure as a generalization of an SVM, which
can be solved efficiently. We further improve computational efficiency by using
a branch-and-bound strategy for localization during both training and testing.
Experimental evaluation on the PASCAL VOC and TU Darmstadt datasets show that
the structured training procedure improves pe rformance over binary training as
well as the best previously published scores.'
alternative_title:
- LNCS
author:
- first_name: Matthew
full_name: Blaschko,Matthew B
last_name: Blaschko
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Blaschko M, Lampert C. Learning to localize objects with structured output
regression. In: Vol 5302. Springer; 2008:2-15. doi:10.1007/978-3-540-88682-2_2'
apa: 'Blaschko, M., & Lampert, C. (2008). Learning to localize objects with
structured output regression (Vol. 5302, pp. 2–15). Presented at the ECCV: European
Conference on Computer Vision, Springer. https://doi.org/10.1007/978-3-540-88682-2_2'
chicago: Blaschko, Matthew, and Christoph Lampert. “Learning to Localize Objects
with Structured Output Regression,” 5302:2–15. Springer, 2008. https://doi.org/10.1007/978-3-540-88682-2_2.
ieee: 'M. Blaschko and C. Lampert, “Learning to localize objects with structured
output regression,” presented at the ECCV: European Conference on Computer Vision,
2008, vol. 5302, pp. 2–15.'
ista: 'Blaschko M, Lampert C. 2008. Learning to localize objects with structured
output regression. ECCV: European Conference on Computer Vision, LNCS, vol. 5302,
2–15.'
mla: Blaschko, Matthew, and Christoph Lampert. Learning to Localize Objects with
Structured Output Regression. Vol. 5302, Springer, 2008, pp. 2–15, doi:10.1007/978-3-540-88682-2_2.
short: M. Blaschko, C. Lampert, in:, Springer, 2008, pp. 2–15.
conference:
name: 'ECCV: European Conference on Computer Vision'
date_created: 2018-12-11T12:04:43Z
date_published: 2008-11-17T00:00:00Z
date_updated: 2021-01-12T07:51:37Z
day: '17'
doi: 10.1007/978-3-540-88682-2_2
extern: 1
intvolume: ' 5302'
main_file_link:
- open_access: '0'
url: http://www.kyb.mpg.de/fileadmin/user_upload/files/publications/attachments/ECCV2008-Blaschko_5247%5b0%5d.pdf
month: '11'
page: 2 - 15
publication_status: published
publisher: Springer
publist_id: '2653'
quality_controlled: 0
status: public
title: Learning to localize objects with structured output regression
type: conference
volume: 5302
year: '2008'
...
---
_id: '3706'
abstract:
- lang: eng
text: We present a new technique for structured prediction that works in a hybrid
generative/discriminative way, using a one-class support vector machine to model
the joint probability of (input, output)-pairs in a joint reproducing kernel Hilbert
space. Compared to discriminative techniques, like conditional random fields or
structured output SVMs?, the proposed method has the advantage that its training
time depends only on the number of training examples, not on the size of the label
space. Due to its generative aspect, it is also very tolerant against ambiguous,
incomplete or incorrect labels. Experiments on realistic data show that our method
works efficiently and robustly in situations that discriminative techniques have
problems with or that are computationally infeasible for them.
author:
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Matthew
full_name: Blaschko,Matthew B
last_name: Blaschko
citation:
ama: 'Lampert C, Blaschko M. Joint kernel support estimation for structured prediction.
In: Curran Associates, Inc.; 2008:1-4.'
apa: 'Lampert, C., & Blaschko, M. (2008). Joint kernel support estimation for
structured prediction (pp. 1–4). Presented at the NIPS SISO: NIPS Workshop on
“Structured Input - Structured Output,” Curran Associates, Inc.'
chicago: Lampert, Christoph, and Matthew Blaschko. “Joint Kernel Support Estimation
for Structured Prediction,” 1–4. Curran Associates, Inc., 2008.
ieee: 'C. Lampert and M. Blaschko, “Joint kernel support estimation for structured
prediction,” presented at the NIPS SISO: NIPS Workshop on “Structured Input -
Structured Output,” 2008, pp. 1–4.'
ista: 'Lampert C, Blaschko M. 2008. Joint kernel support estimation for structured
prediction. NIPS SISO: NIPS Workshop on ‘Structured Input - Structured Output’,
1–4.'
mla: Lampert, Christoph, and Matthew Blaschko. Joint Kernel Support Estimation
for Structured Prediction. Curran Associates, Inc., 2008, pp. 1–4.
short: C. Lampert, M. Blaschko, in:, Curran Associates, Inc., 2008, pp. 1–4.
conference:
name: 'NIPS SISO: NIPS Workshop on "Structured Input - Structured Output"'
date_created: 2018-12-11T12:04:43Z
date_published: 2008-12-12T00:00:00Z
date_updated: 2021-01-12T07:51:37Z
day: '12'
extern: 1
main_file_link:
- open_access: '0'
url: http://agbs.kyb.tuebingen.mpg.de/wikis/bg/siso2008/Blaschkoetal.pdf
month: '12'
page: 1 - 4
publication_status: published
publisher: Curran Associates, Inc.
publist_id: '2650'
quality_controlled: 0
status: public
title: Joint kernel support estimation for structured prediction
type: conference
year: '2008'
...
---
_id: '3712'
abstract:
- lang: eng
text: We present a new method for spectral clustering with paired data based on
kernel canonical correlation analysis, called correlational spectral clustering.
Paired data are common in real world data sources, such as images with text captions.
Traditional spectral clustering algorithms either assume that data can be represented
by a single similarity measure, or by co-occurrence matrices that are then used
in biclustering. In contrast, the proposed method uses separate similarity measures
for each data representation, and allows for projection of previously unseen data
that are only observed in one representation (e.g. images but not text). We show
that this algorithm generalizes traditional spectral clustering algorithms and
show consistent empirical improvement over spectral clustering on a variety of
datasets of images with associated text.
author:
- first_name: Matthew
full_name: Blaschko,Matthew B
last_name: Blaschko
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Blaschko M, Lampert C. Correlational spectral clustering. In: IEEE; 2008:1-8.
doi:10.1109/CVPR.2008.4587353'
apa: 'Blaschko, M., & Lampert, C. (2008). Correlational spectral clustering
(pp. 1–8). Presented at the CVPR: Computer Vision and Pattern Recognition, IEEE.
https://doi.org/10.1109/CVPR.2008.4587353'
chicago: Blaschko, Matthew, and Christoph Lampert. “Correlational Spectral Clustering,”
1–8. IEEE, 2008. https://doi.org/10.1109/CVPR.2008.4587353.
ieee: 'M. Blaschko and C. Lampert, “Correlational spectral clustering,” presented
at the CVPR: Computer Vision and Pattern Recognition, 2008, pp. 1–8.'
ista: 'Blaschko M, Lampert C. 2008. Correlational spectral clustering. CVPR: Computer
Vision and Pattern Recognition, 1–8.'
mla: Blaschko, Matthew, and Christoph Lampert. Correlational Spectral Clustering.
IEEE, 2008, pp. 1–8, doi:10.1109/CVPR.2008.4587353.
short: M. Blaschko, C. Lampert, in:, IEEE, 2008, pp. 1–8.
conference:
name: 'CVPR: Computer Vision and Pattern Recognition'
date_created: 2018-12-11T12:04:45Z
date_published: 2008-09-18T00:00:00Z
date_updated: 2021-01-12T07:51:40Z
day: '18'
doi: 10.1109/CVPR.2008.4587353
extern: 1
month: '09'
page: 1 - 8
publication_status: published
publisher: IEEE
publist_id: '2646'
quality_controlled: 0
status: public
title: Correlational spectral clustering
type: conference
year: '2008'
...
---
_id: '3714'
abstract:
- lang: eng
text: Most successful object recognition systems rely on binary classification,
deciding only if an object is present or not, but not providing information on
the actual object location. To perform localization, one can take a sliding window
approach, but this strongly increases the computational cost, because the classifier
function has to be evaluated over a large set of candidate subwindows. In this
paper, we propose a simple yet powerful branchand- bound scheme that allows efficient
maximization of a large class of classifier functions over all possible subimages.
It converges to a globally optimal solution typically in sublinear time. We show
how our method is applicable to different object detection and retrieval scenarios.
The achieved speedup allows the use of classifiers for localization that formerly
were considered too slow for this task, such as SVMs with a spatial pyramid kernel
or nearest neighbor classifiers based on the 2-distance. We demonstrate state-of-the-art
performance of the resulting systems on the UIUC Cars dataset, the PASCAL VOC
2006 dataset and in the PASCAL VOC 2007 competition.
author:
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Matthew
full_name: Blaschko,Matthew B
last_name: Blaschko
- first_name: Thomas
full_name: Hofmann,Thomas
last_name: Hofmann
citation:
ama: 'Lampert C, Blaschko M, Hofmann T. Beyond sliding windows: Object localization
by efficient subwindow search. In: IEEE; 2008:1-8. doi:10.1109/CVPR.2008.4587586'
apa: 'Lampert, C., Blaschko, M., & Hofmann, T. (2008). Beyond sliding windows:
Object localization by efficient subwindow search (pp. 1–8). Presented at the
CVPR: Computer Vision and Pattern Recognition, IEEE. https://doi.org/10.1109/CVPR.2008.4587586'
chicago: 'Lampert, Christoph, Matthew Blaschko, and Thomas Hofmann. “Beyond Sliding
Windows: Object Localization by Efficient Subwindow Search,” 1–8. IEEE, 2008.
https://doi.org/10.1109/CVPR.2008.4587586.'
ieee: 'C. Lampert, M. Blaschko, and T. Hofmann, “Beyond sliding windows: Object
localization by efficient subwindow search,” presented at the CVPR: Computer Vision
and Pattern Recognition, 2008, pp. 1–8.'
ista: 'Lampert C, Blaschko M, Hofmann T. 2008. Beyond sliding windows: Object localization
by efficient subwindow search. CVPR: Computer Vision and Pattern Recognition,
1–8.'
mla: 'Lampert, Christoph, et al. Beyond Sliding Windows: Object Localization
by Efficient Subwindow Search. IEEE, 2008, pp. 1–8, doi:10.1109/CVPR.2008.4587586.'
short: C. Lampert, M. Blaschko, T. Hofmann, in:, IEEE, 2008, pp. 1–8.
conference:
name: 'CVPR: Computer Vision and Pattern Recognition'
date_created: 2018-12-11T12:04:46Z
date_published: 2008-09-18T00:00:00Z
date_updated: 2021-01-12T07:51:40Z
day: '18'
doi: 10.1109/CVPR.2008.4587586
extern: 1
main_file_link:
- open_access: '0'
url: http://www.kyb.mpg.de/fileadmin/user_upload/files/publications/pdfs/pdf5070.pdf
month: '09'
page: 1 - 8
publication_status: published
publisher: IEEE
publist_id: '2644'
quality_controlled: 0
status: public
title: 'Beyond sliding windows: Object localization by efficient subwindow search'
type: conference
year: '2008'
...
---
_id: '3716'
abstract:
- lang: eng
text: |
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an image purely on a per-class basis. Joint learning of more than one object class would generally be preferable, since this would allow the use of contextual information such as co-occurrence between classes. However, this approach is usually not employed because of its computational cost.
In this paper we propose a method to combine the efficiency of single class localization with a subsequent decision process that works jointly for all given object classes. By following a multiple kernel learning (MKL) approach, we automatically obtain a sparse dependency graph of relevant object classes on which to base the decision. Experiments on the PASCAL VOC 2006 and 2007 datasets show that the subsequent joint decision step clearly improves the accuracy compared to single class detection.
alternative_title:
- LNCS
author:
- first_name: Christoph
full_name: Christoph Lampert
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Matthew
full_name: Blaschko,Matthew B
last_name: Blaschko
citation:
ama: 'Lampert C, Blaschko M. A multiple kernel learning approach to joint multi-class
object detection. In: Vol 5096. Springer; 2008:31-40. doi:10.1007/978-3-540-69321-5_4'
apa: 'Lampert, C., & Blaschko, M. (2008). A multiple kernel learning approach
to joint multi-class object detection (Vol. 5096, pp. 31–40). Presented at the
DAGM: German Association For Pattern Recognition, Springer. https://doi.org/10.1007/978-3-540-69321-5_4'
chicago: Lampert, Christoph, and Matthew Blaschko. “A Multiple Kernel Learning Approach
to Joint Multi-Class Object Detection,” 5096:31–40. Springer, 2008. https://doi.org/10.1007/978-3-540-69321-5_4.
ieee: 'C. Lampert and M. Blaschko, “A multiple kernel learning approach to joint
multi-class object detection,” presented at the DAGM: German Association For Pattern
Recognition, 2008, vol. 5096, pp. 31–40.'
ista: 'Lampert C, Blaschko M. 2008. A multiple kernel learning approach to joint
multi-class object detection. DAGM: German Association For Pattern Recognition,
LNCS, vol. 5096, 31–40.'
mla: Lampert, Christoph, and Matthew Blaschko. A Multiple Kernel Learning Approach
to Joint Multi-Class Object Detection. Vol. 5096, Springer, 2008, pp. 31–40,
doi:10.1007/978-3-540-69321-5_4.
short: C. Lampert, M. Blaschko, in:, Springer, 2008, pp. 31–40.
conference:
name: 'DAGM: German Association For Pattern Recognition'
date_created: 2018-12-11T12:04:46Z
date_published: 2008-07-07T00:00:00Z
date_updated: 2021-01-12T07:51:41Z
day: '07'
doi: 10.1007/978-3-540-69321-5_4
extern: 1
intvolume: ' 5096'
main_file_link:
- open_access: '0'
url: http://www.kyb.mpg.de/fileadmin/user_upload/files/publications/attachments/DAGM2008-Lampert-Blaschko_5072%5b0%5d.pdf
month: '07'
page: 31 - 40
publication_status: published
publisher: Springer
publist_id: '2641'
quality_controlled: 0
status: public
title: A multiple kernel learning approach to joint multi-class object detection
type: conference
volume: 5096
year: '2008'
...
---
_id: '3726'
abstract:
- lang: eng
text: Single-molecule atomic force microscopy (AFM) provides novel ways to characterize
the structure-function relationship of native membrane proteins. High-resolution
AFM topographs allow observing the structure of single proteins at sub-nanometer
resolution as well as their conformational changes, oligomeric state, molecular
dynamics and assembly. We will review these feasibilities illustrating examples
of membrane proteins in native and reconstituted membranes. Classification of
individual topographs of single proteins allows understanding the principles of
motions of their extrinsic domains, to learn about their local structural flexibilities
and to find the entropy minima of certain conformations. Combined with the visualization
of functionally related conformational changes these insights allow understanding
why certain flexibilities are required for the protein to function and how structurally
flexible regions allow certain conformational changes. Complementary to AFM imaging,
single-molecule force spectroscopy (SMFS) experiments detect molecular interactions
established within and between membrane proteins. The sensitivity of this method
makes it possible to measure interactions that stabilize secondary structures
such as transmembrane α-helices, polypeptide loops and segments within. Changes
in temperature or protein-protein assembly do not change the locations of stable
structural segments, but influence their stability established by collective molecular
interactions. Such changes alter the probability of proteins to choose a certain
unfolding pathway. Recent examples have elucidated unfolding and refolding pathways
of membrane proteins as well as their energy landscapes.
author:
- first_name: Andreas
full_name: Engel, Andreas
last_name: Engel
- first_name: Harald L
full_name: Harald Janovjak
id: 33BA6C30-F248-11E8-B48F-1D18A9856A87
last_name: Janovjak
orcid: 0000-0002-8023-9315
- first_name: Dimtrios
full_name: Fotiadis, Dimtrios
last_name: Fotiadis
- first_name: Alexej
full_name: Kedrov, Alexej
last_name: Kedrov
- first_name: David
full_name: Cisneros, David
last_name: Cisneros
- first_name: Daniel
full_name: Mueller, Daniel J
last_name: Mueller
citation:
ama: 'Engel A, Janovjak HL, Fotiadis D, Kedrov A, Cisneros D, Mueller D. Single-molecule
microscopy and force spectroscopy of membrane proteins. In: Single Molecules
and Nanotechnology. Vol 12. Springer; 2008:279-311. doi:10.1007/978-3-540-73924-1_11'
apa: Engel, A., Janovjak, H. L., Fotiadis, D., Kedrov, A., Cisneros, D., & Mueller,
D. (2008). Single-molecule microscopy and force spectroscopy of membrane proteins.
In Single Molecules and Nanotechnology (Vol. 12, pp. 279–311). Springer.
https://doi.org/10.1007/978-3-540-73924-1_11
chicago: Engel, Andreas, Harald L Janovjak, Dimtrios Fotiadis, Alexej Kedrov, David
Cisneros, and Daniel Mueller. “Single-Molecule Microscopy and Force Spectroscopy
of Membrane Proteins.” In Single Molecules and Nanotechnology, 12:279–311.
Springer, 2008. https://doi.org/10.1007/978-3-540-73924-1_11.
ieee: A. Engel, H. L. Janovjak, D. Fotiadis, A. Kedrov, D. Cisneros, and D. Mueller,
“Single-molecule microscopy and force spectroscopy of membrane proteins,” in Single
Molecules and Nanotechnology, vol. 12, Springer, 2008, pp. 279–311.
ista: 'Engel A, Janovjak HL, Fotiadis D, Kedrov A, Cisneros D, Mueller D. 2008.Single-molecule
microscopy and force spectroscopy of membrane proteins. In: Single Molecules and
Nanotechnology. vol. 12, 279–311.'
mla: Engel, Andreas, et al. “Single-Molecule Microscopy and Force Spectroscopy of
Membrane Proteins.” Single Molecules and Nanotechnology, vol. 12, Springer,
2008, pp. 279–311, doi:10.1007/978-3-540-73924-1_11.
short: A. Engel, H.L. Janovjak, D. Fotiadis, A. Kedrov, D. Cisneros, D. Mueller,
in:, Single Molecules and Nanotechnology, Springer, 2008, pp. 279–311.
date_created: 2018-12-11T12:04:50Z
date_published: 2008-01-08T00:00:00Z
date_updated: 2021-01-12T07:51:45Z
day: '08'
doi: 10.1007/978-3-540-73924-1_11
extern: 1
intvolume: ' 12'
month: '01'
page: 279 - 311
publication: Single Molecules and Nanotechnology
publication_status: published
publisher: Springer
publist_id: '2503'
quality_controlled: 0
status: public
title: Single-molecule microscopy and force spectroscopy of membrane proteins
type: book_chapter
volume: 12
year: '2008'
...
---
_id: '3734'
abstract:
- lang: eng
text: Gene expression levels fluctuate even under constant external conditions.
Much emphasis has usually been placed on the components of this noise that are
due to randomness in transcription and translation. Here we focus on the role
of noise associated with the inputs to transcriptional regulation; in particular,
we analyze the effects of random arrival times and binding of transcription factors
to their target sites along the genome. This contribution to the total noise sets
a fundamental physical limit to the reliability of genetic control, and has clear
signatures, but we show that these are easily obscured by experimental limitations
and even by conventional methods for plotting the variance vs. mean expression
level. We argue that simple, universal models of noise dominated by transcription
and translation are inconsistent with the embedding of gene expression in a network
of regulatory interactions. Analysis of recent experiments on transcriptional
control in the early Drosophila embryo shows that these results are quantitatively
consistent with the predicted signatures of input noise, and we discuss the experiments
needed to test the importance of input noise more generally.
acknowledgement: NSF Grant PHY-0650617; NIH grants P50 GM071508, R01 GM077599; Burroughs
Wellcome Program in Biological Dynamics
author:
- first_name: Gasper
full_name: Gasper Tkacik
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
- first_name: William
full_name: Bialek, William S
last_name: Bialek
citation:
ama: Tkačik G, Gregor T, Bialek W. The role of input noise in transcriptional regulation.
PLoS One. 2008;3(7). doi:10.1371/journal.pone.0002774
apa: Tkačik, G., Gregor, T., & Bialek, W. (2008). The role of input noise in
transcriptional regulation. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0002774
chicago: Tkačik, Gašper, Thomas Gregor, and William Bialek. “The Role of Input Noise
in Transcriptional Regulation.” PLoS One. Public Library of Science, 2008.
https://doi.org/10.1371/journal.pone.0002774.
ieee: G. Tkačik, T. Gregor, and W. Bialek, “The role of input noise in transcriptional
regulation,” PLoS One, vol. 3, no. 7. Public Library of Science, 2008.
ista: Tkačik G, Gregor T, Bialek W. 2008. The role of input noise in transcriptional
regulation. PLoS One. 3(7).
mla: Tkačik, Gašper, et al. “The Role of Input Noise in Transcriptional Regulation.”
PLoS One, vol. 3, no. 7, Public Library of Science, 2008, doi:10.1371/journal.pone.0002774.
short: G. Tkačik, T. Gregor, W. Bialek, PLoS One 3 (2008).
date_created: 2018-12-11T12:04:52Z
date_published: 2008-07-23T00:00:00Z
date_updated: 2021-01-12T07:51:49Z
day: '23'
doi: 10.1371/journal.pone.0002774
extern: 1
intvolume: ' 3'
issue: '7'
license: https://creativecommons.org/licenses/by/4.0/
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2475664
month: '07'
oa: 1
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '2498'
quality_controlled: 0
status: public
title: The role of input noise in transcriptional regulation
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
volume: 3
year: '2008'
...
---
_id: '3739'
abstract:
- lang: eng
text: 'Changes in a cell''s external or internal conditions are usually reflected
in the concentrations of the relevant transcription factors. These proteins in
turn modulate the expression levels of the genes under their control and sometimes
need to perform nontrivial computations that integrate several inputs and affect
multiple genes. At the same time, the activities of the regulated genes would
fluctuate even if the inputs were held fixed, as a consequence of the intrinsic
noise in the system, and such noise must fundamentally limit the reliability of
any genetic computation. Here we use information theory to formalize the notion
of information transmission in simple genetic regulatory elements in the presence
of physically realistic noise sources. The dependence of this "channel capacity"
on noise parameters, cooperativity and cost of making signaling molecules is explored
systematically. We find that, in the range of parameters probed by recent in vivo
measurements, capacities higher than one bit should be achievable. It is of course
generally accepted that gene regulatory elements must, in order to function properly,
have a capacity of at least one bit. The central point of our analysis is the
demonstration that simple physical models of noisy gene transcription, with realistic
parameters, can indeed achieve this capacity: it was not self-evident that this
should be so. We also demonstrate that capacities significantly greater than one
bit are possible, so that transcriptional regulation need not be limited to simple
"on-off" components. The question whether real systems actually exploit
this richer possibility is beyond the scope of this investigation.'
author:
- first_name: Gasper
full_name: Gasper Tkacik
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Curtis
full_name: Callan,Curtis G
last_name: Callan
- first_name: William
full_name: Bialek, William S
last_name: Bialek
citation:
ama: Tkačik G, Callan C, Bialek W. Information capacity of genetic regulatory elements.
Physical Review E Statistical Nonlinear and Soft Matter Physics. 2008;78(1).
doi:10.1103/PhysRevE.78.011910
apa: Tkačik, G., Callan, C., & Bialek, W. (2008). Information capacity of genetic
regulatory elements. Physical Review E Statistical Nonlinear and Soft Matter
Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.78.011910
chicago: Tkačik, Gašper, Curtis Callan, and William Bialek. “Information Capacity
of Genetic Regulatory Elements.” Physical Review E Statistical Nonlinear and
Soft Matter Physics. American Institute of Physics, 2008. https://doi.org/10.1103/PhysRevE.78.011910.
ieee: G. Tkačik, C. Callan, and W. Bialek, “Information capacity of genetic regulatory
elements,” Physical Review E Statistical Nonlinear and Soft Matter Physics,
vol. 78, no. 1. American Institute of Physics, 2008.
ista: Tkačik G, Callan C, Bialek W. 2008. Information capacity of genetic regulatory
elements. Physical Review E Statistical Nonlinear and Soft Matter Physics. 78(1).
mla: Tkačik, Gašper, et al. “Information Capacity of Genetic Regulatory Elements.”
Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 78,
no. 1, American Institute of Physics, 2008, doi:10.1103/PhysRevE.78.011910.
short: G. Tkačik, C. Callan, W. Bialek, Physical Review E Statistical Nonlinear
and Soft Matter Physics 78 (2008).
date_created: 2018-12-11T12:04:54Z
date_published: 2008-07-21T00:00:00Z
date_updated: 2021-01-12T07:51:51Z
day: '21'
doi: 10.1103/PhysRevE.78.011910
extern: 1
intvolume: ' 78'
issue: '1'
month: '07'
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '2488'
quality_controlled: 0
status: public
title: Information capacity of genetic regulatory elements
type: journal_article
volume: 78
year: '2008'
...
---
_id: '3740'
abstract:
- lang: eng
text: In the simplest view of transcriptional regulation, the expression of a gene
is turned on or off by changes in the concentration of a transcription factor
(TF). We use recent data on noise levels in gene expression to show that it should
be possible to transmit much more than just one regulatory bit. Realizing this
optimal information capacity would require that the dynamic range of TF concentrations
used by the cell, the input/output relation of the regulatory module, and the
noise in gene expression satisfy certain matching relations, which we derive.
These results provide parameter-free, quantitative predictions connecting independently
measurable quantities. Although we have considered only the simplified problem
of a single gene responding to a single TF, we find that these predictions are
in surprisingly good agreement with recent experiments on the Bicoid/Hunchback
system in the early Drosophila embryo and that this system achieves approximately
90% of its theoretical maximum information transmission.
acknowledgement: P50 GM071508/GM/NIGMS NIH HHS/United States; R01 GM077599/GM/NIGMS
NIH HHS/United States
author:
- first_name: Gasper
full_name: Gasper Tkacik
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Curtis
full_name: Callan,Curtis G
last_name: Callan
- first_name: William
full_name: Bialek, William S
last_name: Bialek
citation:
ama: Tkačik G, Callan C, Bialek W. Information flow and optimization in transcriptional
regulation. PNAS. 2008;105(34):12265-12270. doi:10.1073/pnas.0806077105
apa: Tkačik, G., Callan, C., & Bialek, W. (2008). Information flow and optimization
in transcriptional regulation. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.0806077105
chicago: Tkačik, Gašper, Curtis Callan, and William Bialek. “Information Flow and
Optimization in Transcriptional Regulation.” PNAS. National Academy of
Sciences, 2008. https://doi.org/10.1073/pnas.0806077105.
ieee: G. Tkačik, C. Callan, and W. Bialek, “Information flow and optimization in
transcriptional regulation,” PNAS, vol. 105, no. 34. National Academy of
Sciences, pp. 12265–12270, 2008.
ista: Tkačik G, Callan C, Bialek W. 2008. Information flow and optimization in transcriptional
regulation. PNAS. 105(34), 12265–12270.
mla: Tkačik, Gašper, et al. “Information Flow and Optimization in Transcriptional
Regulation.” PNAS, vol. 105, no. 34, National Academy of Sciences, 2008,
pp. 12265–70, doi:10.1073/pnas.0806077105.
short: G. Tkačik, C. Callan, W. Bialek, PNAS 105 (2008) 12265–12270.
date_created: 2018-12-11T12:04:54Z
date_published: 2008-01-01T00:00:00Z
date_updated: 2021-01-12T07:51:52Z
day: '01'
doi: 10.1073/pnas.0806077105
extern: 1
intvolume: ' 105'
issue: '34'
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2527900
month: '01'
oa: 1
page: 12265 - 12270
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '2489'
quality_controlled: 0
status: public
title: Information flow and optimization in transcriptional regulation
type: journal_article
volume: 105
year: '2008'
...
---
_id: '3744'
abstract:
- lang: eng
text: It is widely acknowledged that detailed timing of action potentials is used
to encode information, for example, in auditory pathways; however, the computational
tools required to analyze encoding through timing are still in their infancy.
We present a simple example of encoding, based on a recent model of time-frequency
analysis, in which units fire action potentials when a certain condition is met,
but the timing of the action potential depends also on other features of the stimulus.
We show that, as a result, spike-triggered averages are smoothed so much that
they do not represent the true features of the encoding. Inspired by this example,
we present a simple method, differential reverse correlations, that can separate
an analysis of what causes a neuron to spike, and what controls its timing. We
analyze with this method the leaky integrate-and-fire neuron and show the method
accurately reconstructs the model's kernel.
author:
- first_name: Gasper
full_name: Gasper Tkacik
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Marcelo
full_name: Magnasco, Marcelo O
last_name: Magnasco
citation:
ama: 'Tkačik G, Magnasco M. Decoding spike timing: The differential reverse-correlation
method. Biosystems. 2008;93(1-2):90-100. doi:10.1016/j.biosystems.2008.04.011'
apa: 'Tkačik, G., & Magnasco, M. (2008). Decoding spike timing: The differential
reverse-correlation method. Biosystems. Elsevier. https://doi.org/10.1016/j.biosystems.2008.04.011'
chicago: 'Tkačik, Gašper, and Marcelo Magnasco. “Decoding Spike Timing: The Differential
Reverse-Correlation Method.” Biosystems. Elsevier, 2008. https://doi.org/10.1016/j.biosystems.2008.04.011.'
ieee: 'G. Tkačik and M. Magnasco, “Decoding spike timing: The differential reverse-correlation
method,” Biosystems, vol. 93, no. 1–2. Elsevier, pp. 90–100, 2008.'
ista: 'Tkačik G, Magnasco M. 2008. Decoding spike timing: The differential reverse-correlation
method. Biosystems. 93(1–2), 90–100.'
mla: 'Tkačik, Gašper, and Marcelo Magnasco. “Decoding Spike Timing: The Differential
Reverse-Correlation Method.” Biosystems, vol. 93, no. 1–2, Elsevier, 2008,
pp. 90–100, doi:10.1016/j.biosystems.2008.04.011.'
short: G. Tkačik, M. Magnasco, Biosystems 93 (2008) 90–100.
date_created: 2018-12-11T12:04:56Z
date_published: 2008-07-01T00:00:00Z
date_updated: 2021-01-12T07:51:53Z
day: '01'
doi: 10.1016/j.biosystems.2008.04.011
extern: 1
intvolume: ' 93'
issue: 1-2
main_file_link:
- open_access: '1'
url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2792887
month: '07'
oa: 1
page: 90 - 100
publication: Biosystems
publication_status: published
publisher: Elsevier
publist_id: '2482'
quality_controlled: 0
status: public
title: 'Decoding spike timing: The differential reverse-correlation method'
type: journal_article
volume: 93
year: '2008'
...
---
_id: '3751'
abstract:
- lang: eng
text: 'Revealing the spectrum of combinatorial regulation of transcription at individual
promoters is essential for understanding the complex structure of biological networks.
However, the computations represented by the integration of various molecular
signals at complex promoters are difficult to decipher in the absence of simple
cis regulatory codes. Here we synthetically shuffle the regulatory architecture-operator
sequences binding activators and repressors-of a canonical bacterial promoter.
The resulting library of complex promoters allows for rapid exploration of promoter
encoded logic regulation. Among all possible logic functions, NOR and ANDN promoter
encoded logics predominate. A simple transcriptional cis regulatory code determines
both logics, establishing a straightforward map between promoter structure and
logic phenotype. The regulatory code is determined solely by the type of transcriptional
regulation combinations: two repressors generate a NOR: NOT (a OR b) whereas a
repressor and an activator generate an ANDN: a AND NOT b. Three-input versions
of both logics, having an additional repressor as an input, are also present in
the library. The resulting complex promoters cover a wide dynamic range of transcriptional
strengths. Synthetic promoter shuffling represents a fast and efficient method
for exploring the spectrum of complex regulatory functions that can be encoded
by complex promoters. From an engineering point of view, synthetic promoter shuffling
enables the experimental testing of the functional properties of complex promoters
that cannot necessarily be inferred ab initio from the known properties of the
individual genetic components. Synthetic promoter shuffling may provide a useful
experimental tool for studying naturally occurring promoter shuffling.'
article_number: e2030
author:
- first_name: Ali
full_name: Kinkhabwala, Ali
last_name: Kinkhabwala
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Kinkhabwala A, Guet CC. Uncovering cis regulatory codes using synthetic promoter
shuffling. PLoS One. 2008;3(4). doi:10.1371/journal.pone.0002030
apa: Kinkhabwala, A., & Guet, C. C. (2008). Uncovering cis regulatory codes
using synthetic promoter shuffling. PLoS One. Public Library of Science.
https://doi.org/10.1371/journal.pone.0002030
chicago: Kinkhabwala, Ali, and Calin C Guet. “Uncovering Cis Regulatory Codes Using
Synthetic Promoter Shuffling.” PLoS One. Public Library of Science, 2008.
https://doi.org/10.1371/journal.pone.0002030.
ieee: A. Kinkhabwala and C. C. Guet, “Uncovering cis regulatory codes using synthetic
promoter shuffling,” PLoS One, vol. 3, no. 4. Public Library of Science,
2008.
ista: Kinkhabwala A, Guet CC. 2008. Uncovering cis regulatory codes using synthetic
promoter shuffling. PLoS One. 3(4), e2030.
mla: Kinkhabwala, Ali, and Calin C. Guet. “Uncovering Cis Regulatory Codes Using
Synthetic Promoter Shuffling.” PLoS One, vol. 3, no. 4, e2030, Public Library
of Science, 2008, doi:10.1371/journal.pone.0002030.
short: A. Kinkhabwala, C.C. Guet, PLoS One 3 (2008).
date_created: 2018-12-11T12:04:58Z
date_published: 2008-04-30T00:00:00Z
date_updated: 2021-01-12T07:51:56Z
day: '30'
ddc:
- '570'
doi: 10.1371/journal.pone.0002030
extern: '1'
external_id:
pmid:
- '18446205'
file:
- access_level: open_access
checksum: 42c26f8337298a9ecadbe34a16139466
content_type: application/pdf
creator: dernst
date_created: 2019-05-10T11:00:36Z
date_updated: 2020-07-14T12:46:15Z
file_id: '6400'
file_name: 2008_PLOS1_Kinkhabwala.PDF
file_size: 679786
relation: main_file
file_date_updated: 2020-07-14T12:46:15Z
has_accepted_license: '1'
intvolume: ' 3'
issue: '4'
language:
- iso: eng
license: https://creativecommons.org/publicdomain/zero/1.0/
month: '04'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '2477'
quality_controlled: '1'
status: public
title: Uncovering cis regulatory codes using synthetic promoter shuffling
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2008'
...
---
_id: '3754'
abstract:
- lang: eng
text: Fluorescence correlation spectroscopy (FCS) has permitted the characterization
of high concentrations of noncoding RNAs in a single living bacterium. Here, we
extend the use of FCS to low concentrations of coding RNAs in single living cells.
We genetically fuse a red fluorescent protein (RFP) gene and two binding sites
for an RNA-binding protein, whose translated product is the RFP protein alone.
Using this construct, we determine in single cells both the absolute [mRNA] concentration
and the associated [RFP] expressed from an inducible plasmid. We find that the
FCS method allows us to reliably monitor in real-time [mRNA] down to similar to
40 nM (i.e. approximately two transcripts per volume of detection). To validate
these measurements, we show that [mRNA] is proportional to the associated expression
of the RFP protein. This FCS-based technique establishes a framework for minimally
invasive measurements of mRNA concentration in individual living bacteria.
acknowledgement: 'PMCID: PMC2475643 '
author:
- first_name: Calin C
full_name: Calin Guet
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Luke
full_name: Bruneaux,Luke
last_name: Bruneaux
- first_name: Taejin
full_name: Min,Taejin L
last_name: Min
- first_name: Dan
full_name: Siegal-Gaskins,Dan
last_name: Siegal Gaskins
- first_name: Israel
full_name: Figueroa,Israel
last_name: Figueroa
- first_name: Thierry
full_name: Emonet,Thierry
last_name: Emonet
- first_name: Philippe
full_name: Cluzel,Philippe
last_name: Cluzel
citation:
ama: Guet CC, Bruneaux L, Min T, et al. Minimally invasive determination of mRNA
concentration in single living bacteria. Nucleic Acids Research. 2008;36(12).
doi:10.1093/nar/gkn329
apa: Guet, C. C., Bruneaux, L., Min, T., Siegal Gaskins, D., Figueroa, I., Emonet,
T., & Cluzel, P. (2008). Minimally invasive determination of mRNA concentration
in single living bacteria. Nucleic Acids Research. Oxford University Press.
https://doi.org/10.1093/nar/gkn329
chicago: Guet, Calin C, Luke Bruneaux, Taejin Min, Dan Siegal Gaskins, Israel Figueroa,
Thierry Emonet, and Philippe Cluzel. “Minimally Invasive Determination of MRNA
Concentration in Single Living Bacteria.” Nucleic Acids Research. Oxford
University Press, 2008. https://doi.org/10.1093/nar/gkn329.
ieee: C. C. Guet et al., “Minimally invasive determination of mRNA concentration
in single living bacteria,” Nucleic Acids Research, vol. 36, no. 12. Oxford
University Press, 2008.
ista: Guet CC, Bruneaux L, Min T, Siegal Gaskins D, Figueroa I, Emonet T, Cluzel
P. 2008. Minimally invasive determination of mRNA concentration in single living
bacteria. Nucleic Acids Research. 36(12).
mla: Guet, Calin C., et al. “Minimally Invasive Determination of MRNA Concentration
in Single Living Bacteria.” Nucleic Acids Research, vol. 36, no. 12, Oxford
University Press, 2008, doi:10.1093/nar/gkn329.
short: C.C. Guet, L. Bruneaux, T. Min, D. Siegal Gaskins, I. Figueroa, T. Emonet,
P. Cluzel, Nucleic Acids Research 36 (2008).
date_created: 2018-12-11T12:04:59Z
date_published: 2008-01-01T00:00:00Z
date_updated: 2021-01-12T07:51:57Z
day: '01'
doi: 10.1093/nar/gkn329
extern: 1
intvolume: ' 36'
issue: '12'
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '01'
publication: Nucleic Acids Research
publication_status: published
publisher: Oxford University Press
publist_id: '2474'
quality_controlled: 0
status: public
title: Minimally invasive determination of mRNA concentration in single living bacteria
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
volume: 36
year: '2008'
...