Below are some of the current CBB students and their research.
Jamie's research has been focused on understanding the targeting mechanisms of activation induced cytosine deaminase (AID), which is responsible for somatic hypermutation in germinal center B-cells. Her lab has recently been working to identify cis-regulatory modules which are responsible for recruiting AID to the immunoglobulin loci and other recently identified genes. The goal is to identify why some genes are targets of AID and others are not and additionally why some of the mutated genes are repaired in an error-free manner as opposed to other genes that are repaired in an error-prone manner.
Emmett works on creating system models of breast cancer pathology, with a focus on HER2+ breast cancers. He is currently investigating copy number variations in different patients, as well as HER2+ breast cancer cell lines.
Mohamed's research involves computational analysis of the immune system. Specifically, he is studying Immunoglobulin (Ig) receptor sequences and lineage trees.
Pedro is studying yeast genes that are essential to its quiescent state by integrating various data sources, such as gene expression studies, sub-cellular protein localization, and protein-protein interaction networks. He is also working on demonstrating the important relationships between quiescence and human neurodegenerative diseases.
Ray is working on several projects including: 1) Analyzing results from ChIP-Sequencing experiments to locate novel transcription factor binding site patterns in the human and worm genomes, 2) developing new methods to analyze large datasets inherent in next-generation sequencing and metagenomics experiments, and 3) applying existing biological information/annotations to the results of ChIP-Seq experiments. He has also helped develop a new scoring method for ChIP-Seq data as well as a method to analyze data from barcoded libraries on the Illumina next-generation sequencing platform.
Becky is studying comparative genomics among multiple species, including worm, fly, human and yeast. She is reviewing different ortholog resources that are available to help determine a final gene pair list. She is also looking at available tandem mass spectrometry data to try to determine a new way to confirm possible genome annotations.
Taiwo's research focuses on the development and application of statistical and computational methods to identify genomic biomarkers of response to trastuzumab-based therapy. He's interested in clinical and translational research and is currently working on integrating gene expression, protein expression and copy number data to identify pertinent predictors of response to therapy.
Jasmine's work mainly focuses on developing computational tools and frameworks for characterizing human genomic variations and analyzing evolutionary forces on functional elements. These methods can be applied to next generation sequencing data, and help elucidating genetic difference between personal genomes, as well as individuals with disease.
Christopher's research centers around the response of Hepatitis C to treatment with Interferon. The main goal of his research is to understand the mechanisms that differentiate patients who respond to treatment from patients who do not. He is also looking at designing methods for pinpointing the source of a differential gene expression signature in a mixed cell population.
Xiaowei's research focus is genome wide association studies and analysis of next generation sequencing data. She is currently working on a cancer resequencing project to identify the ovarian-cancer-related variations in 3' UTRs and microRNAs. She is also working with Clip-seq data to find the RNAs interacting with protein Lin-28.
Jane's research focuses on developing computational methods for studying the evolution of transcriptional regulation using comparative and functional genomics data. Specifically, understanding the dynamics of enhancer/promoter utilization cross species and their impact on gene expression using comparative genomics and ChIP-seq, RNA-seq data.
Lucas' current research involves investigating the saturation of human transcription factor binding sites (TFBSes) with chromatin immunoprecipitation sequencing (ChIP-seq) of human cell lines used in the ENCODE project. He has also worked on using expression levels of interacting gene networks to predict prostate cancer phenotypes.
Haisu is interested in the analysis of human gene coexpression networks using microarray data. She is also involved in the DREAM4 project to reconstruct gene regulatory networks from simulated steady-state and time�series data.
Kelly is studying erythrocytes and leukemia and particularly a cohort of RNA-sequence data. He is trying to identify alternative splice events and fusion proteins and determine their role in pathogenesis. He is also studying myeloid lineages and K562 siRNA knockdowns. He is working with and developing genome assembly algorithms. Finally he is looking at ways to process reads from RNA-seq that do not require assembly.
Mengjie is working on an extended multivariate Bayesian Change Point (BCP) model to segment the Drosophila melanogaster genome to consecutive blocks on the basis of combinatorial patterns of histone marks. The aim is to understand more about orchestrated regulation and genome organization.
Daniel is studying the antibody repertoire of humans. He is currently working on computational and graph-theoretic methods to sort into clonal lineages immunoglobulin data obtained from next-generation sequencing of blood samples. He also aims to study mutation patterns and track changes in the selection pressures acting upon these clones which may arise in response to antigen exposure.
Vijay is studying the development and application of kernel methods and semi-supervised learning methods to extract information from the narrative text of the electronic medical record. He is developing methods to integrate domain knowledge encoded in biomedical ontologies with machine learning techniques to classify medical text.
Matt is interested in the use of semantic technology and automated reasoning to draw new conclusions from high-throughput biological data. Current projects include the integration of functional genomic information from the Gene Ontology and pathway repositories with quantitative omics data from clinical cancer research. Additionally, Matt is working on using temporal reasoning to create a highly scalable semantic resource for analyzing genomic sequence.
Jieming's interests lie at the intersection between genomics, protein engineering, systems and synthetic biology and at the interface of experimental and computational research. Currently, he attempts to explore protein-protein interactions by integrating molecular features in proteins (atoms, structures, hydrophobicity, affinity, binding energy etc.) with systems-level information (networks, genomes etc.).
Yao is interested in correlating human genomic variation data with the properties of networks. She is also interested in the prediction of gene functions, such as predicting cell cycle regulated genes.
Xiu's research involves assessing the effectiveness of a kind of Chinese medicine PHY906 by comparing gene expression profiles under different conditions and in different tissues to infer the pathways involved in the functional process of PHY906.
Cong is building statistical models to predict one's genetic predisposition to common diseases by integrating high-dimensional genomic data. In particular, he is looking for methods that best recover the 'missing heritability' in the context of genetic risk prediction.
Leon's focus is to study the functional cause of Autism Spectrum Disorder (ASD), a severe neurodevelopmental disorder. He is trying to integrate independent data sources, including whole-exome sequencing on autism families, gene expression and microarray genotyping data.
Hanyu's work focuses mainly on the meta-analysis of data coming from different subgroups. Specifically, she is working to develop a Bayesian model to study the patterns of heterogeneity in these datasets.
Gili's research interests revolve around genomics, computational immunology and pathology. Her current research focuses on correlating structural variations (e.g., copy number variations) to common human diseases.
Dissertation: "Informatics Approaches to Translational Research: Management and Analysis of Clinical and High Density Genomic Data"
Dissertation: "Statistical Modeling of Biological Interactions in Eukaryotes using Genomics and Proteomics Data"
Dissertation: "Tiling Microarray Informatics"
Dissertation: "Mapping Regulatory Networks Using Genomic and Proteomic Approaches"
Dissertation: "Genomic Studies on Nuclear Receptor-Mediated Transcriptional Networks in Breast Cancer Cells"
Dissertation: "Mining Biological Complexity: Cross Integration of Large-Scale Metagenomics, Environmental, and Chemical Datasets"
Dissertation: "Integration of Genomic Data to Identify Genes and Pathways Associated with Disease"
Dissertation: "High-throughput Methods in Computer-aided Drug Design Pertaining to Flexibility, Selectivity and Lipophilicity"
Dissertation: "High-dimensional Gene expression Classification and genome-wide association Studies of Complex Traits"
Dissertation: "Computational Analysis on Genomic Variation: Detecting and Characterizing Structural Variants in the Human Genome"
Dissertation: "Semi-automated Model Building for RNA Crystallography: A Directed Rotameric Approach to Building the RNA Backbone"
Dissertation: "Translational Epigenetics: Applications of High-Throughput Genomic Technologies for Melanoma Diagnostics and Treatment"
Dissertation: "Integrating Genomic and Kinetic Data to Elucidate Mechanisms of Alcohol Dependence"
Dissertation: "Towards Intelligent Integration of Information from High-Throughput Studies of Human Genomes"
Dissertation: "Predicting drug response and function using sub-structure analysis."
Dissertation: "Computational Analysis on Biological Networks:Measuring Evolutionary Rewiring & Predicting Regulatory Relationship"
Dissertation: "Building Risk Prediction Model for Complex Genetic Disease Using High Dimensional Genetic Data."
Dissertation: "Piecewise Constant Estimation: Extensions of PartDSA and Applications to Cancer and Epidemiological Studies"
Dissertation: "Improving Biomedical Information Retrieval Using Term Identification and Concurrent Image and Text Processing"
Dissertation: "Overcoming Complexity in Systems Biology Modeling and Simulation"
Dissertation: "Computational Methodologies for Transcript Analysis in the Age of Next-Generation DNA Sequencing"