Pacific Symposium on Biocomputing workshop on cellular heterogeneity

July 31, 2012 § Leave a comment

The Pacific Symposium on Biocomputing will be held on the Big Island of Hawaii from January 3 to 7, 2013, and our very own Eric Batchelor (well, he used to be ours) is co-organizing the workshop described below.  You can submit abstracts here (requires sign-up).

PSB 2013 Workshop: Modeling cell heterogeneity: from single-cell variations to mixed cell populations

Co-chairs: Eric Batchelor, Maricel G. Kann, Teresa M. Przytycka, Ben Raphael, and Damian Wojtowicz

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: August 31st, 2012

Speaker notification: September 15th, 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.

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