The program involves over 20 core bioinformatics faculty leading research in:
- Prediction of protein structure, function, interaction networks
- Transcriptomics via RNAseq
- Epigenomics (high-throughput methylation profiling)
- Genome-wide association for disease genes
- Stochastic network inference and modeling
- Population genomics
- Bayesian phylogenetics and comparative genomics
- Genome evolution
- Algorithmic development for high-throughput data-mining
| Michael Alfaro (Computational) | Diversification and Macroevolution, Evolutionary Morphology, Theoretical Phylogenetics, Reef Fish Molecular Systematics |
| Giovanni Coppola (Experimental) | Genetic, epigenetic, and gene expression studies in neurodegenerative dementias (frontotemporal dementia, Alzheimer’s disease) and other neuropsychiatric diseases. |
| Joseph Distefano (Computational) | Dynamic systems biology modeling |
| David Eisenberg (Experimental) | Protein structure, folding and design. |
| Jason Ernst (Computational) | Machine learning methods for the analysis of high-throughput experimental data to address problems in epigenomics and gene regulation. |
| Eleazar Eskin (Computational) | Bioinformatics, Statistical Genetics, Genetic Basis of Complex Traits. (see seminar video: Integrated genomics approaches for analyzing complex traits in inbred mice; see another seminar video) |
| Guoping Fan (Experimental) | Epigenetic mechanisms in neural development and stem cell regulation |
| Nelson Freimer (Experimental) | Genetics of complex traits [neurobehavioral, metabolic, and infectious], population genomics, neurogenomics, primate systems biology and comparative evolution. Center for Neurobehavioral Genetics |
| Dan Geschwind (Experimental) | application of network analyses, systems biology, and integration of multiple levels of data, to molecular pathways for nervous system function in health and disease |
| Thomas Graeber (Experimental) | Systems Biology of Cancer Signaling |
| David Heckerman (Computational) | Statistics and data analysis, machine learning, probability theory,decision theory, decision analysis, and artificial intelligence. Using graphical models for data analysis and visualization in biology and medicine with a special focus on the design of HIV vaccines and genome-wide association studies. |
| Stefan Horvath (Computational) | Statistical analysis of DNA and tissue microarray data (see seminar video: Consensus eigengene networks: studying gene co‐expression modules and networks) |
| Steve Jacobsen (Experimental) | Molecular genetics and genomics of DNA methylation patterning. |
| James Lake (Computational) | Genomics and bioinformatics, including the evolution and origin of genomes (see seminar video) |
| Kenneth Lange (Computational) | Human genetics, population biology, biomedical imaging, computational statistics, and applied stochastic processes |
| Christopher Lee (Computational) | Bioinformatics, Genome Evolution, Alternative Splicing (see seminar video; more talks) |
| Huiying Li (Experimental) | Human microbiome and diseases, Metagenomics, Bioinformatics, Systems biology |
| Kerchau Li (Computational) | Bioinformatics, systems biology, High dimensional data analysis, network study, microarray gene expression, microRNA expression analysis, array CGH, biomarker, eQTL, Maldi-Seldi protein profile analysis (see seminar video: Liquid Association: a new bioinformatics tool for exploring gene expression data) |
| Jamie Lloyd-Smith (Computational) | Ecological and evolutionary dynamics of infectious disease in animal and human populations, with emphasis on zoonotic and emerging pathogens. |
| Kirk Lohmueller (Computational) | Development and application of statistical methods in evolutionary and medical genetics; learning about demographic history from genetic variation data; understanding natural selection. |
| Stanley Nelson (Experimental) | Genomics approaches to human disease (see seminar video: Genomic approaches to human diseases: new tools and opportunities) |
| John Novembre (Computational) | Computational methods in population genetics; human evolutionary genetics; genome evolution; population structure and adaptation (see seminar video: New results from studies of human and canid population genomics; A collective living stockpile of biological information: lessons and chellenges from population genomics) |
| Paivi Pajukanta (Experimental) | Integration of genomics, transcriptomics and functional approaches to investigate human cardiovascular disease. |
| Bogdan Pasaniuc (Computational) | Computational and statistical methods for understanding the genetic architecture of common diseases; analysis of large scale sequencing-based studies with a special emphasis on admixed populations. |
| Matteo Pellegrini (Computational) | Computational methods to interpret genomic data (see seminar video) |
| Peipei Ping (Experimental) | Proteome biology of cardiovascular diseases; cardiovascular proteome knowledgebase (www.heartproteome.org); informatics model systems for performing global proteomic analyses in human diseases; NHLBI Proteomics Center (www.nhlbi-ucla.org). |
| Kathrin Plath (Experimental) | Epigenetic mechanisms of stem cell renewal, differentiation, and cancer |
| Janet Sinsheimer (Computational) | Statistical methodology for mapping complex trait and disease genes and for understanding evolution |
| Marc Suchard (Computational) | Stochastic processes in biology; Evolutionary medicine; Statistical computing (see seminar video) |
| Paul Thompson (Computational) | Genetic Analysis of Massive Imaging Databases (http://www.loni.ucla.edu/~thompson/IG/IG.html),Mathematics of Images and Genomes (http://www.loni.ucla.edu/~thompson/MATH/math.html), ENIGMA Project (largest imaging-genetics study in the world) (http://www.youtube.com/watch?v=crmk4UuSeEg&feature=plcp&list=PL7D3E6C9C8F233DD9), Analyzing Brain Connectivity Networks (http://www.loni.ucla.edu/~thompson/MEDIA/AUT/AUT-PR.html) |
| Zhuowen Tu (Computational) | Medical Imaging, Machine Learning, Statistical modeling/computing, and Computer Vision |
| Wei Wang (Computational) | Data mining, computational genetics, protein structure analysis, protein protein interaction networks. |
| Xinshu Grace Xiao (Computational) | Computational and Systems Biology of Pre-mRNA Splicing and Gene Expression |
| Yi Xing (Computational/Experimental) | Computational and statistical methods for elucidating transcriptome complexity and post-transcriptional RNA processing; evolution and genetic diversity of transcriptome regulation; genomics and bioinformatics of pre-mRNA alternative splicing and polyadenylation; RNA regulatory networks in development and disease. |
| Xia Yang (Computational/experimental) | Integrative Genomics and Systems Biology of Common Metabolic Disorders |
| Todd Yeates (Computational) | Structures of large protein assemblies, including the carboxysome and other bacterial microcompartment shells; applications of geometry and topology to proteins; discovery of protein function through comparative genomics. (see seminar video) |
| Qing Zhou (Computational) | Computational biology, Monte Carlo methods and Bayesian statistics (see seminar video: Model Discovery via Contrasting Sequence Sets with Applications to Genome-wide Binding Data; Extracting sequence features to predict protein-DNA interactions) |