Seminar Series Abstracts

Fridays at 11am.

September 25, 2009 Emma Lundberg Royal Institute of Technology, Stockholm homepage

A Human Protein Atlas

Information on protein localization and expression on tissue, cell and organelle level is important to map and characterize the human proteome as well as to better understand cellular functions of proteins and to find biomarkers. In the Human Protein Atlas program the human proteome is systematically analyzed using an antibody-based approach. By generation and thorough validation of antibodies, protein localization and expression in human tissues and cells can be analyzed using immunohistochemistry and fluorescence confocal microscopy. The results are publicly available in the Human Protein Atlas web portal (www.proteinatlas.org) that currently contains results from the use of more than 8,800 validated antibodies corresponding to one third of all human genes. The portal contains more than 7 million high-resolution images that each has been manually annotated and curated by a certified pathologist or a cell biologist to provide a knowledge base for functional studies and to allow searches and queries about protein profiles in normal and disease tissue as well as on a cell and subcellular level. Advanced queries can be performed, including searches for chromosome location, protein class and/or tissue specificity (including the 20 most common forms of human cancer), facilitating for instance biomarker discovery. Our results suggest that it should be possible to extend the protein atlas to cover the majority of all human proteins thus providing a valuable tool for biological and medical research.
October 2, 2009 Hagit Shatkay Queen's University homepage

Life by the Book: Pragmatically Using Text in Large Scale -Omics.

The genomic era, in which we live since the sequencing of the human genome, is characterized by tremendous amounts of biomedical data, accompanied by a significant increase in the number of related scientific publications.
Much biomedical knowledge is hidden within the abundant literature. The ability to rapidly and effectively survey the literature can support numerous applications, including multiple stages in the design and the interpretation of large-scale experiments.
A variety of methods are being applied to the biomedical literature in an attempt to meet these goals, mostly through careful mining of text for gene/protein names and interactions, using natural language processing methods. However, the idea of general "biomedical text mining" remains elusive.
Rather than view biomedical text mining as one monolithic (and not very well defined) task, we attend to specific biological goals that may benefit from the use of text. The talk will focus on several biological applications/problems involving text, and discuss some non-traditional, coarse-grain methods, that we use to address them.
October 9, 2009 Bhaskar DasGupta University of Illinois at Chicago homepage

Synthesizing and simplifying biological networks from pathway level information

Cellular networks involve a complex "wireless" interaction propagating siganls between individual components such as DNAs, RNAs and smaller molecules. Recent (and sometimes not-so-recent) surge of interest in investigation of these networks have resulted in fascinating inter-disciplinary collaborations between several disciplines such as biology, control theory, mathematics and computer science.
In this talk, I will summarize the research works that my collaborators and myself have been doing in the last few years in this area. We will discuss about synthesizing and simplifying networks from double-causal experimental data, reverse engineering such networks via modular-response-analysis approach or from time-series data and modular decomposition of such networks into simpler networks. We will present the relevant biological background, explain the dynamic processes (models) that may arise, discuss combinatorial and graph-theoretic algorithmic questions that arise out of designing experimental protocols or optimizing such networks and present computational results. Minimal prior knowledge in control theory or combinatorial algorithms will be assumed.
The results discussed are prior or ongoing joint research works with one or more of the following collaborators (listed in alphabetical order): Reka Albert, Piotr Berman, German Enciso, Sema Kachalo, Paola Vera-Licona, Eduardo Sontag, Kelly Westbrooks, Alexander Zelikovsky, Ranran Zhang and Yi Zhang.
October 23, 2009 David Baker University of Washington homepage

From Prediction of Structure to Design of Function

I will describe our recent progress in predicting protein structures from their amino acid sequences, and in designing proteins with new folds and functions. We can now compute the energies of different protein conformations sufficiently accurately that the bottleneck to consistent high accuracy structure prediction is conformational sampling. With even a very small amount of experimental data, the sampling problem becomes much more tractable and we are now able to compute structures quite accurately using such limited datasets, for example backbone only NMR data and low resolution electron density maps. With Rosetta@home, we can now carry out very large scale mapping of protein folding landscapes, and quite intriguingly we find that the lowest energy structures are not exactly coincident with crystal structures, particularly in loop regions, which leads to the somewhat heretical speculation that the computed structures may in some cases be more accurate models for proteins in solution. I will also discuss the design of novel enzymes catalyzing four different chemical bond breaking and forming reactions. Finally, I will describe results on structure prediction and design challenges obtained by people playing the online competitive game fold.it.
October 30, 2009 Naren Ramakrishnan Virginia Tech homepage

How do I remember thee? Let me count the ways.

How does a cell know what type of cell it is supposed to become? How do external chemical signals change the underlying state of the cell? How are response pathways triggered on the application of a stress? Such questions of differentiation, signal transduction, and stress response, while seemingly diverse, all pertain to the storage of state information, or memory, by biochemical switches. Just as a computer memory unit can store a bit of 0 or 1 through electrical signals, a biochemical switch is a bistable circuit that uses chemical signals to flip state. Only a small number of cellular switches have been described and analyzed, and several of these are highly non-intuitive in their function. This suggests that there might be some novel ways for a biochemical network to "remember".
In this study we count the ways. Using numerical homotopy continuation methods coupled with data mining algorithms, we explore all possible chemical networks up to a modest level of complexity, looking for bistable circuits and "motifs" that give rise to bistability. Based on the small number of known switches, and the immensity of reaction parameter space, we expected to find very few bistable switches. Instead, we find enormous numbers, reaching 20% of all configurations for sufficiently large systems. We also discovered that many of the non-bistable circuits can be altered according to a simple algorithm, to also become bistable. Finally, we show how our catalog of switches can be organized into a "family tree" thus suggesting some evolutionary implications. Our work opens up new bioinformatics challenges to use switches and other computing metaphors to comprehend complex signaling systems.
November 6, 2009 Peter Park Children's Hospital, Boston homepage

ChIP-sequencing: data analysis and applications

ChIP-seq combines chromatin immunoprecipitation (ChIP) with next-generation sequencing to identify protein-DNA interactions on a genome-wide scale. After a brief introduction to next-generation sequencing, a number of practical issues in analysis of ChIP-seq data will be discussed, including experimental design, detection of binding sites, and determination of whether a sufficient depth of sequencing has been achieved. Application of ChIP-seq to the study of X-chromosome dosage compensation in Drosophila and nucleosome positioning will be described. If time allows, updates from the Cancer Genome Atlas and the model organism ENCODE projects will be given.
November 13, 2009 Shirley Luckhart University of California, Davis homepage

The potential for application of systems biology to modeling malaria parasite-host interactions

Malaria is perhaps the most ancient and most devastating infectious disease humankind has ever known – current estimates indicate that 300-500 million new infections occur every year. Our work on this complex disease has been focused for nearly 15 years on understanding how ingested mammalian growth factors and cytokines regulate signaling and malaria parasite infection at the dual host interface of malaria transmission. Our long-term goal is to manipulate a highly complex ecological system – which consists of the mosquito host, the mammalian host, and the malaria parasite – as a whole in order to block malaria infection. This work led to our intensive study of cell signaling pathways that regulate transmission, guided by advances in the field of mammalian immunity and inflammation. In mammals, four interacting regulatory pathways are associated with immunity: the nuclear factor (NF)-?B pathway and the three mitogen-activated protein kinase (MAPK) pathways, including JNK, ERK and p38-dependent pathways. The inflammatory outcomes driven by these signaling pathways set in motion new signals that must be interpreted by all three members of this ecosystem. This challenge is daunting, given the complexity of the inflammatory response in a single species. Yet, we propose that this complexity can be addressed rationally through inter-connected experimental approaches and computational simulations. This integrated approach will allow us to discern not only the mechanisms operant in the process of immune crosstalk, but also explain unexpected behavior in the system and define the “master switches” – the crosstalking extracellular factors and signaling pathway components – that have the greatest potential impact on malaria parasite transmission.
November 6, 2009 Gregoire Altan-Bonnet Memorial Sloan-Kettering Cancer Center homepage

System Imunobiology: how integrated cytokine regulation enforces self/non-self discrimination in the immune system

Understanding how the immune system decides between tolerance and response to antigens requires addressing cytokine regulation as a highly dynamic process. Here we present results assessing quantitatively the dynamic competition for IL-2 between regulatory T cells (Treg) and effector T cells (Teff), by combining in silico modeling and in vitro experiments with single-cell resolution. We demonstrate how elevated IL-2 receptor levels increase T cells~R ability to bind IL-2: for Treg cells, this implies higher depletion efficiency; for Teff cells, this leads to stronger survival signals and resistance to IL-2 depletion. Furthermore, we show how Treg cells limit the proliferation and survival signals in Teff cells by reducing not only the amount of available IL-2 but also their ability to sense it. Finally, we demonstrate that Treg and Teff cells engage in an IL-2 tug-of-war resulting in specific suppression of survival signals for weakly activated Teff cells, but not for strongly activated ones.
December 4, 2009 Eddie Holmes Penn State University homepage

Life on the Edge: The Evolutionary Biology of RNA Viruses

RNA viruses are of great biological importance because of their role as agents of human disease and their presumed similarity to some of the earliest replicating molecules. In this seminar I will present an overview of the 'rules' of evolutionary change in RNA viruses. The fulcrum of my talk is a hypothesis that the major aspects of RNA evolution and life-history - from the way they organize their genomes to their ability to jump species boundaries - reflect an intrinsically high rate of mutation. For example, I will show that the process of genome evolution in RNA viruses is in a large part determined by a remarkably high rate of deleterious mutation, which acts to put a cap on maximum genome size. This, in turn, means that the evolution of RNA viruses is characterized by complex fitness trade-offs and epistatic interactions, and which greatly impacts on their ability to emerge in new host species. Similarly, I will show that the rates of recombination and patterns of genome organization in RNA viruses also reflect aspects of their mutational burden. Finally, I will argue that high rates of mutation also provide indirect evidence that RNA viruses have their evolutionary origins with the early replicators of the 'RNA world'.
January 15, 2010 homepage

January 22, 2010 homepage

January 29, 2010 Quaid Morris University of Toronto homepage

February 5, 2010 homepage

February 12, 2010 homepage

February 19, 2010 Daniel Erlanson Carmot Therapeutics, Inc. homepage

February 26, 2010 homepage

March 5, 2010 homepage

March 19, 2010 Rohit Pappu Washington University in St. Louis homepage

March 26, 2010 Nancy Amato Texas A&M University homepage

April 2, 2010 Mona Singh Princeton University homepage

April 9, 2010 Wendy Cornell Merck homepage

April 23, 2010 Michael Q. Zhang Cold Spring Harbor Laboratory homepage

April 30, 2010 Tandy Warnow Univ. of Texas at Austin homepage

© 2008 Joint Carnegie Mellon - University of Pittsburgh PhD Program in Computational Biology (CPCB)