Gary Benson
Associate Professor

Ph.D. University of Maryland 1992 computer science

M.S. University of Maryland 1989 computer science

B.S. University of Maryland 1976 psychology

Contact Info:

Gary Benson
Associate Professor
Departments of Biology and Computer Science
Program in Bioinformatics
Boston University
Rm 903
24 Cummington St.
Boston, MA 02215
Tel: 617-358-2965
Fax: 617-353-4814
Email: Gary Benson




My research focus is algorithm development for sequence analysis, in particular

  • detection and analysis of DNA repeats and
  • analysis of multiple sequence alignments (both protein and DNA) for functional and structural information.


Tandem Repeats. A tandem repeat is an occurrence of two or more adjacent, often approximate copies of a sequence of nucleotides. As an example, consider the following visualization of a tandem repeat taken from the Tandem Repeats Database (TRDB). The blue line is the consensus pattern and the 19 red lines are the individual copies within the repeat, one copy per line. Only differences with respect to the pattern are shown. Note the redundant mutations which suggest that this repeat has undergone several rounds of expansion.

Tandem repeats are ubiquitous sequence features in both prokaryotic and eukaryotic genomes. In humans, they are known to cause at least ten inherited neurological diseases including fragile-X mental retardation, Huntington's disease, and myotonic dystrophy and are associated with a number of other major illnesses, including diabetes, epilepsy, and ovarian and other cancers. Additionally, they are the basis of DNA fingerprinting and have recently been used to discriminate between different bacterial strains, including anthrax strains.

Detecting approximate tandem repeats had been a difficult open problem. Pattern sizes vary from a few nucleotides to well over 1000 and conservation between the copies can be lower than 70 percent. In order to address this need, I developed the Tandem Repeats Finder which employs a stochastic model of tandem repeats and associated statistical detection criteria. It is extremely fast and thorough, and is now regularly used to analyze new genomic sequences.

TRDB. Tandem repeats remain a neglected class despite their ubiquity and known functional roles. Information sources are incomplete, fragmented and difficult for researchers to access. The Tandem Repeats Finder has simplified the task of identifying repeats (for example, analysis of C. elegans with a genome of approximately 100 million bases takes 60 minutes and finds ~25,000 tandem repeats) opening the way for more detailed analysis. I am in the early stages of building a multi-genome database (TRDB) of tandem repeats. Ongoing work includes: 1) clustering repeats into families, 2) developing sequence based predictive criteria for copy number polymorphism, 3) automating the annotation of repeats and families, and 4) implementing user interface and data visualization tools.

Other Repeats. I am working on methods to detect low-copy repeats, which occur as non-adjacent copies, and composition repeats which occur as variations in DNA composition rather than as `word' patterns. The former contribute to many types of disease and the latter may have regulatory and/or structural effects.

Extracting information from multiple sequence alignments. Alignment of many related sequences from viral or bacterial quasi-species can reveal important information about proteins, RNA, and DNA, including changes that correlate with pathogenicity, drug susceptibility and sequence structure. Extracting this information, manually, from multiple alignments is often difficult, especially when a large number of long sequences are utilized. In collaboration with researchers at Mount Sinai, I have been developing Mutation Master a set of computer analysis tools which rapidly provide a visual display and tabulation of site, frequency, number and likelihood of point mutations. Analysis of hepatitus C virus (HCV) protein sequences using Mutation Master has identified possible sites of amino acid structural interaction, and has revealed that ARFP, a novel protein encoded in an overlapping reading frame, is as conserved as conventional HCV proteins. Ongoing work includes developing similar tools to analyze RNA multiple alignments for structural clues including compensatory mutations.


I have been teaching for 20 years, the first 8 as a high school mathematics teacher and the remainder as a graduate teaching assistant, postdoc and assistant professor in computer science. My area of expertise and main interest in teaching is theoretical computer science/algorithms with applications in biology, i.e., computational biology and bioinformatics.

While at Mount Sinai, I have developed and taught graduate level courses with a focus on biological sequence analysis. These include Computational Structural Biology and Advanced Topics in Computational Molecular Biology. Topics covered in the advanced course include: 1) sequence alignment algorithms, 2) scoring functions and substitution matrices for alignment, 3) database search algorithms (BLAST and FASTA), 4) multiple alignment, 5) hidden Markov models and their application to gene detection, and 6) algorithms for finding unknown repetitive patterns in sequences (enumeration, Monte Carlo and statistical methods). I am currently developing another course Pattern Detection Techniques for Biological Sequences which incorporates topics in pattern detection for sequences as well as methods for expression array analysis.

I have served as advisor/mentor for graduate students and have hosted several undergraduate and high school students in my lab during summers at Mount Sinai. I participated in NSF Young Scholars programs as a guest lecturer and served as co-director of the Villanova Summer Research Institute in Biology, Computing and Mathematics. I am currently collaborating on the development of high school curriculum modules related to computational biology as part of the Gateway to Higher Education program in New York City.

I support outreach efforts to attract and train minority students and underrepresented groups and have actively participated in such activities through the Mount Sinai summer fellowship program, the Mount Sinai Hospital Placement program for high school students and the New York City Alliance for Minority Participation in Science Engineering and Mathematics.


  Quick Links:

Composition Alignment: download | web | sim
TRF : download | web
IRF : download
FHub | CHub
K'nex DNA Models

  Latest News:

New Vntrseek 1.05 version is now available for download.
New TRF 4.07b version is now available for download.
IRF command line version is now available for download.

  Page last updated:11/29/12