CALL FOR PARTICIPATION:
Short description:
Emerging
technologies such as single cell gene expression analysis and single cell
genome sequencing provide an unprecedented opportunity to quantitatively probe
biological interactions at the single cell level. This new level of insight has
begun to reveal a more accurate picture of cellular behavior, and to highlight
the importance of understanding cellular variation in a wide range of
biological contexts. The aim of this workshop is to bring together researchers
working on identifying and modeling cell heterogeneity that arises by a variety
of mechanisms, including but not limited to cell-to-cell noise, cell-state
switches and cell differentiation, heterogeneity in immune responses, cancer
evolution, and heterogeneity in disease progression. We will welcome algorithms
to process single-cell experimental data and to provide a system-level view of
the interplay of diverse, fluctuating biological components.
Call for participation:
Quantifying
the molecular mechanisms underlying cellular behaviors and functions is one of
the ultimate goals of biology and medicine. Until recently, most characterization
of cellular behavior has been performed on the average of all cells in a sample
instead of on individual cells. However, measurements derived from pooled
populations of cells can mask the true behavior of individual cells and lack
the specificity to capture outlier cell behavior that might explain cell
differentiation and transitions from normal to disease cellular states.
Emerging
technologies such as single cell gene expression analysis and single cell
genome sequencing provide an unprecedented opportunity to quantify single cell
level differences. These technologies will provide a wealth of new information
at single-cell resolution, including protein abundance,
methylation patterns, promoter structure, gene expression, copy number
variations, gene function and essentiality, DNA structure, evolutionary
plasticity, and selective advantage.
These data can all be leveraged in the quest to understand the emergence
and consequences of cell heterogeneity.
The
focus of this section is on identifying and modeling cell heterogeneity that
arises by any of the above-mentioned mechanisms – sporadically,
programmed, and through evolution. Some examples of topics covered in this
session will be questions related to:
- cell-to-cell noise
-
cell-state switches and cell differentiation
-
heterogeneity in immune responses
-
cancer evolution
-
heterogeneity in disease
progression
-
algorithms to process
single-cell experimental data
Abstracts
We are soliciting abstracts of
published and unpublished work (up to 500 words) related to the topics
mentioned above. The workshop will combine invited talks, talks selected
from abstract submissions to this call, and a panel discussion.
Please submit abstracts online at https://www.easychair.org/conferences/?conf=psbmch2013
Important dates
Abstract deadline: September 7,
2012
Speaker notification: September 22,
2012
All speakers should be registered to
PSB 2013 by October 1st, 2012.
Workshop organizers:
Eric Batchelor,
Ph.D. is an
Investigator in the Center for Cancer Research, National Cancer Institute,
National Institutes of Health (NIH). He recently joined the NIH as one of the
first Earl Stadtman Investigators, following graduate
work in the Physics Department at the University of Pennsylvania and
postdoctoral studies in the Systems Biology Department at Harvard Medical
School. His research uses a combination of experimental and computational
approaches to quantitatively understand the regulation and function of
mammalian stress responses. His work emphasizes single cell-level analysis of
the regulatory motifs that control stress signaling
dynamics. His recent work has focused on the dynamical response of the tumor
suppressor p53 upon activation by various forms of DNA damage. His areas of
expertise include long-term time-lapse fluorescence microscopy, single-cell
level variability, and dynamical systems.
Maricel
Kann, Ph.D. is an assistant professor at the University of Maryland, Baltimore
County. Her research interests include integration of sequence-based with
predictors of protein–protein interactions and other technologies for the
classification of human variants and diseases. She is one of the leading
experts in the area of translational Bioinformatics, an associate editor of
Journal of Biomedical Informatics, and has chaired several international conferences,
including several PSB sessions.
Teresa M. Przytycka,
Ph.D. is a
Senior Investigator at the National Center for Biotechnology Information, NIH.
She is heading a research group focusing on developing algorithmic and graph
theoretical approaches to study problems arising in Computational and Systems
Biology. Dr. Przytycka's research interests
include: biological networks, gene
regulation, phenotypic variability and systems level modeling of
genotype-phenotype associations. She serves as an associate editor of PloS Computational Biology, IEEE Transactions of
Bioinformatics, BMC-Bioinformatics. She has chaired a number of conferences
including PSB session on network dynamics, ISMB Comparative Genomics section,
WABI 2012 conference, and 2010 Keystone meeting on Systems Biology and
Diseases.
Ben Raphael, Ph.D. is an Associate Professor
of Computer Science at Brown University.
His research interests include the design and application of algorithms
to study human genomic variation and somatic evolution in cancer. His recent work has focused on finding
driver mutations in cancer genomes, including approaches that address both
inter- and intra-tumor heterogeneity.
He is co-founder and a member of the Steering Committee for RECOMB
Computational Cancer Biology (RECOMB-CCB) meeting and have served on Program
Committees for numerous computational biology / bioinformatics conferences.
Damian Wojtowicz,
Ph.D. is a
Postdoctoral Visiting Fellow in the Computational Biology Branch of National
Center for Biotechnology Information, NIH. Before joining NIH, he graduated
from University of Warsaw (Poland), where he subsequently held an assistant
professor position. His research is focused on function and evolution of DNA
structure, gene regulation, protein and genome evolution, as well as on
developing and applying bioinformatics approaches to problems in computational
biology.