Quantitative Foundations of Computational Biology

Key to Computational Biology are the approaches and algorithms for processing, analyzing and modeling knowledge, information and data, that are relevant to research questions from across the life sciences. The development of mathematical and computational methods with probabilistic, statistical, combinatorial, or heuristic foundations continue to drive innovation in Bioinformatics and Systems Biology.

Niema Moshiri

Faculty Status
Active
Title
Assistant Teaching Professor
Email
a1moshir@ucsd.edu
Phone
(619) 993-1642
Track(s)
Bioinformatics and Systems Biology
Biomedical Informatics
Brief Research Description
Computational HIV epidemiology, phylogenetics, models of sequence and tree evolution, Massive Adaptive Interactive Text (MAIT) development
Lab Description

We are interested in developing scalable methods for performing epidemiological analyses of large viral (primarily HIV) sequence and phylogenetic datasets. Topics of interest include large-scale phylogenetic analyses, developing novel models of sequence and tree evolution, performing epidemiological simulation experiments, and developing methods for predicting epidemic outcomes.

Ludmil Alexandrov

Faculty Status
Active
Title
Assistant Professor
Title 2
Assistant Professor
Email
l2alexandrov@ucsd.edu
Phone
(858) 246-2747
Track(s)
Bioinformatics and Systems Biology
Department 2
Brief Research Description
Using large-scale omics data to study mutational processes causing human cancer, identify potential cancer prevention strategies, and develop novel approaches for targeted cancer treatment.

Jill Mesirov

Faculty Status
Active
Title
Professor
Title 2
Associate Vice Chancellor, Computational Health Sciences
Title 3
Professor of Medicine
Email
jmesirov@ucsd.edu
Phone
(858) 534-5096
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Algorithms and analytic methodologies for pattern recognition and discovery with applications to cancer genomics, to better diagnose, stratify, and treat patients. Development of biologist-friendly biomedical software tools.

Graham McVicker

Faculty Status
Active
Title
Assistant Professor
Email
gmcvicker@salk.edu
Phone
(858) 453-4100
Track(s)
Bioinformatics and Systems Biology
Brief Research Description
Human genetic variation, chromatin and gene regulation in immune cells
Lab Description

The McVicker laboratory aims to understand how chromatin state and organization are encoded by the human genome. Our approach to this problem is to exploit naturally occurring human genetic variation to identify sequence variants that disrupt chromatin function. We are currently focused on chromatin within immune cells and we are also interested in how variants that affect chromatin and gene regulation lead to disease risk. The problems that we work on often require the development of sophisticated computational and statistical methods that can extract subtle signals from noisy experimental data.

Siavash Mirarab

Faculty Status
Active
Title
Assistant Professor
Email
smirarabbaygi@ucsd.edu
Phone
858-822-6245
Track(s)
Bioinformatics and Systems Biology
Brief Research Description
Computational biology, large scale phylogenetics, estimation of species trees from gene trees (phylogenomics), large scale multiple sequence alignment, and metagenomic analysis using phylogenetic placement.
Lab Description

Our lab specializes in reconstruction of evolutionary histories (phylogenies) from large scale datasets and applications of phylogenetic analyses to downstream analyses. Large-scale datasets include those with many genes and those with many species, and we focus on high accuracy and scalability at the same time. Many projects in this area are available, some of which are described below, but students can contact me to start on other projects as well.

Debashis Sahoo

Faculty Status
Active
Title
Assistant Professor
Phone
(858) 246-1803
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Systems Biology of normal and cancer tissues, Boolean analysis of biological systems, Computational models of stem cell differentiation, Sequencing data analysis

Saket Navlakha

Faculty Status
Active
Title
Assistant Professor
Email
navlakha@salk.edu
Phone
(858) 453-4100 x2247
Track(s)
Bioinformatics and Systems Biology
Brief Research Description
Algorithms in nature, biological networks and systems biology, information processing and computation in biological systems
Lab Description

We are interested in the interface of theoretical computer science and systems biology. By thinking computationally about the goals, constraints, and algorithmic strategies used by biological systems, we hope to advance both computer science (by developing new bio-inspired algorithms) and biology (by raising testable hypotheses and developing theory and models to predict system behavior).

Vikas Bansal

Faculty Status
Active
Title
Assistant Professor
Email
vibansal@ucsd.edu
Phone
(858) 246-1810
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Computational tools for variant calling, haplotyping and analysis of rare variants in disease association studies
Lab Description

Research in our lab is focused on developing computational methods for the discovery and analysis of human genetic variation using high-throughput sequencing technologies. We develop algorithms and software tools for accurate and comprehensive assembly of human genomes and identifying disease associated variants.

Konrad Scheffler

Faculty Status
Inactive
Title
Associate Professor
Email
kscheffler@ucsd.edu
Phone
(619) 543-6347
Track(s)
Bioinformatics and Systems Biology
Department
Brief Research Description
Probabilistic models of molecular evolution
Lab Description

The Viral Evolution Group (located near the UCSD hospital in Hillcrest) studies computational and statistical models of evolution, with applications to viral pathogens and other systems. Solid programming skills and knowledge of probabilistic modeling (e.g. as covered in CSE250A and CSE250B) are required. There is no wet lab component.