Alexander Alekseyenko, Ph.D.

Research Assistant Professor, Department of Medicine, Division of Clinical Pharmacology, NYU School of Medicine

Dr Alekseyenko is a leading participant in the effort of CHIBI and NYU to harness next generation sequencing technologies for applications in medical and basic science research. His is the primary informatics faculty working in the area of understanding the microbiomic diversity present in the human body through utilization and development of evolutionary and ecological statistical models.

Dr. Alekseyenko's training includes rigorous mathematical, computational and biological components, which puts him into a position to understand the problems of modern biomedical research from multiple perspectives and to speak the language of multiple disciplines. The synthesis of these disciplines during Dr. Alekseyenko’s graduate research yielded an extensive database of alternative splicing events and effective full-genome scale evolutionary models for splicing signaling. This research generated much interest in the community marked by invitations to give lectures at places such as NCBI, Scripps Research Institute, Universities of Oxford, Bristol and Bath. After receiving his Ph.D. in Biomathematics from University of California Los Angeles, Dr. Alekseyenko has continued to postdoctoral training first at EMBL -- European Bioinformatics Institute, Cambridge, UK and then at Stanford University Statistics Department.

To date some notable contributions include: (a) development of highly efficient genome-scale databases for sequence annotation query; (b) derivation of a unifying framework multi-state stochastic Dollo for modeling evolutionary traits encompassing both reversible and irreversible changes; (c) development of accurate and fast methods for stochastic kinetic simulations; (d) sizable effort in open source scientific software projects, such as Bayesian Evolutionary Analysis by Sampling Trees (BEAST) and Python graph database framework (PyGr).

Specific theoretical work currently underway includes: (a) models for sequencing errors in amplified datasets; (b) methods for de novo assembly of heterogeneous samples; (c) phylogenetic tree statistics for fast filtering of “interesting” sequence sites.

Address:
333 E. 38th Street -- 6th Floor
New York University Langone Medical Center
New York, NY 10016, USA
Phone: +1-212-263-3642
Fax: +1-212-263-4885

Email: Alexander.Alekseyenko@nyumc.org