Student Research Presentations
Thursdays at 4:30pm.
| Date/Location | Speaker/Specialization/Advisor |
Sep. 10, 2009 |
Jacob Joseph - Computational Genomics, Dannie Durand Family classification without domain chainingMotivation: Classification of gene and protein sequences into homologous families, i.e. sets of sequences that share common ancestry, is an essential step in comparative genomic analyses. This is typically achieved by construction of a sequence homology network, followed by clustering to identify dense subgraphs corresponding to families. Accurate classification of single domain families is now within reach due to major algorithmic advances in remote homology detection and graph clustering. However, classification of multidomain families remains a significant challenge. The presence of the same domain in sequences that do not share common ancestry introduces false edges in the homology network that link unrelated families and stymy clustering algorithms.Results: Here, we investigate a network-rewiring strategy designed to eliminate edges due to promiscuous domains. We show that this strategy can reduce noise in and restore structure to artificial networks with simulated noise, as well as to the yeast genome homology network. We further evaluate this approach on a hand-curated set of multidomain sequences in mouse and human, and demonstrate that classification using the rewired network delivers dramatic improvement in Precision and Recall, compared with current methods. Families in our test set exhibit a broad range of domain architectures and sequence conservation, demonstrating that our method is flexible, robust and suitable for high-throughput, automated processing of heterogeneous, genome-scale data. | Sep. 17, 2009 |
Justin Hogg - Cell and Systems Modeling, James Faeder Unraveling Sepsis: a systems model provides a hypothesis for dysfunctional neutrophil recruitment and the efficacy of blood purification therapySepsis is a serious medical condition defined by systemic inflammation and the presence of infection. Inflammation plays a key role in recruiting an innate immune response and controlling the infection. Yet, in the septic patient, inflammation may lead to multiple organ dysfunction and possible death. Underlying sepsis is a complex network of interactions occurring at many scales: molecules, cells, and organs. In order to explore the system behavior of sepsis, a compartmental, rule-based model of sepsis was constructed. In particular, the model was designed to address two observations in the experimental literature. First, in a comparison of sub-lethal and lethal sepsis, neutrophil recruitment to the site of infection declines in the lethal model while recruitment to the lung increases. Second, in animal models of sepsis, blood purification therapy improves survival. Model simulations suggest that competitive neutrophil recruitment to healthy tissues leads to depletion of circulating neutrophils and an attenuated response at the infection site. Furthermore, the model demonstrates that filtration of inflammatory mediators from the blood reduces competitive recruitment and potentiates neutrophil recruitment to the primary infection. These results motivate a set of new experiments that will validate or reject the hypothesized mechanisms. | Oct. 1, 2009 |
Lidio Meireles - Computational Structural Biology, Ivet Bahar Fragment-Based Drug Discovery: An Overview of Concepts Fragment-based drug discovery (FBDD) has been recognized as a fruitful strategy to lead discovery, specially when high-throughput screening (HTS) fails to deliver new chemotypes. FBDD consists in first detecting weakly binding small molecular fragments (MW < 250 Da) to subsequently elaborate them into potent binders. In this talk, I will introduce the main concepts underlying FBDD, such as the thermodynamics advantages of combining fragments, the biophysical methods to detect them, fragment library design, ligand efficiency, the better sampling of the chemical space, and the strategies to combine fragments into potent binders, i.e., fragment growing, linking and merging. | Oct. 8, 2009 |
Luis Pedro Coelho - Bioimage Informatics, Robert F. Murphy RandTag: Proteome-wide study of protein subcellular location RandTag is a collaborative project to look at subcellular location data
generated by Central Dogma tagging of proteins. Due to the random nature of
random tagging, repeated application of the experimental procedure results in
different proteins being tagged. Therefore, this enables high-throughput
collection of fluorescently tagged proteins, with endogenous expression.
| Oct. 15, 2009 |
Rachel Brower-Sinning - Computational Genomics, Takis Benos The Potential Role of Folding Energy on Prokaryotic Genomic Evolution
Previously, we showed how the folding free energy of the RNA segments might play an important role in the evolution and host adaptation of the influenza A virus. In this talk, we will show how the folding free energy of the RNA species may also be an important evolutionary force in prokaryotic cells.
| Oct. 22, 2009 |
Suvraji Maji - Computational Structural Biology, Marcel Bruchez Toward Multicolor Three-Dimensional Single Molecule Localization
Single molecule methods such as particle localization and tracking have evolved into one of the most powerful methods in biophysical research. These methods allow us to study the dynamics of complex heterogeneous systems as living cell at single molecule level. The ability to obtain information of individual molecules using single particle tracking (SPT) has opened up new avenues that were previously not possible using ensemble techniques. However, meaningful biological studies using SPT requires an extremely precise localization of single molecules in three dimensions.
| Nov. 5, 2009 |
Ying Liu - Computational Structural Biology, Ivet Bahar A Tale of Two Models: Pre-existing Equilibrium vs. Induced Fit The competition between the ``pre-existing equilibrium'' and ``induced fit'' model for interpreting allosteric conformational change has recently drawn tremendous attention from the biomedical research community. The complexity of biomolecules, in terms of both structure and function, make it impossible to make a binary decision on a general basis. In this presentation I will review some representative work conducted along this line, and introduce several cases that I have been working on. | Nov. 12, 2009 |
Chao Ma - Computational Structural Biology, Xiang-Qun (Sean) Xie | Nov. 19, 2009 |
John Arul Prakash Sekar - Computational Structural Biology, James Faeder | Dec. 10, 2009 | Kyaw (Kujo) Zeyar Myint - Computational Structural Biology, Xiang-Qun (Sean) Xie
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