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Fran Lewitter, Head of Biocomputing, Whitehead Institute


AT A GLANCE: PhD in human biology/ genetics from the University of Colorado, Boulder.

Worked on the GenBank project during its first five years and the first release of the Genome Database. Co-founded the Genetic Counseling program at Brandeis University. Built a biocomputing department to support Whitehead’s basic research labs.

Enjoys hiking, tennis, and playing the double bass.

QWhere will bioinformatics be in two years? Five years?

AWithin two to five years we’ll have the finished sequence of both human and mouse and probably some other primates and mammals. This will let us ask evolutionary questions which were not possible before and will let us look at the differences and similarities among species to gain a better understanding of ourselves. We will have tools to identify the function of proteins and tools to understand protein-protein interactions.

QWhat are the biggest challenges the field of bioinformatics faces?

AI believe the biggest challenge is educating the biologists in the use of computational tools. This includes not only teaching people what tools are available and how to use them, but teaching them how to interpret the results, the algorithms used, and the pros and cons of different methods.

Other challenges include developing software to address some nagging questions: how to predict and characterize human promoter sequence, how to predict structure of a protein from the sequence, and how to evaluate the data gathered in microarray experiments.

QHow do you compete with companies to attract and retain qualified bioinformaticists?

AIn the part of Whitehead I support, there are 20 individual labs working in diverse areas of biomedical research. We get to work with cutting edge researchers involved with state-of-the-art research.

Whitehead provides a wonderful environment in which to learn and grow. Excellent seminars are always available here and across the street at MIT. Also people in my group get to move around on different projects. This seems more appealing to some than getting locked into one long-term project.

QWhat hardware do you use?

AWe currently have several Sun servers and will shortly be implementing a Linux compute farm.

QWhat bioinformatics software do you use?

AWe try to acquire a wide variety of software. We use both commercial and public domain software. Unfortunately there is no one solution to meet all needs of all researchers. Given the directions in which research projects can move, we need to be ready to provide the necessary tools.

We have several desktop products for the Macintosh and PC including but not limited to Sequencher, MacVector, LaserGene and VectorNTI. On our Unix systems we use the standard set of tools — both WU Blast and NCBI Blast, EMBOSS, Genscan, HMMER, University of Washington sequence assembly programs, CLUSTALX and many others.

QHow would you compare the quality of publicly available and commercially available bioinformatics products?

AThe commercial products are generally easier to use because more emphasis has been put on the interface and documentation. However, the functionality is often limited. It is not as easy to change parameters. There is little room for customization when using commercial software. Software that is publicly available, especially those running under Unix, are more easily customizable.

QWhat made you decide to become a bioinformaticist?

AIt was a natural progression for me. I was a mathematics major as an undergraduate and studied genetic epidemiology as a graduate student and postdoc. After spending an additional three years managing my own NIH R01 grant, I decided we weren’t learning more about the genetics of complex traits using the genetic epidemiological tools available in the late 70s and early 80s. It was at that time that the GenBank Project started. It intrigued me and I joined it and worked on the project during its first five years. I got involved with sequence analysis and molecular databases and never looked back.

Filed under

The Scan

Myotonic Dystrophy Repeat Detected in Family Genome Sequencing Analysis

While sequencing individuals from a multi-generation family, researchers identified a myotonic dystrophy type 2-related short tandem repeat in the European Journal of Human Genetics.

TB Resistance Insights Gleaned From Genome Sequence, Antimicrobial Response Assays

Researchers in PLOS Biology explore M. tuberculosis resistance with a combination of sequencing and assays looking at the minimum inhibitory concentrations of 13 drugs.

Mendelian Disease Genes Prioritized Using Tissue-Specific Expression Clues

Mendelian gene candidates could be flagged for further functional analyses based on tissue-specific transcriptome and proteome profiles, a new Journal of Human Genetics paper says.

Single-Cell Sequencing Points to Embryo Mosaicism

Mosaicism may affect preimplantation genetic tests for aneuploidy, a single-cell sequencing-based analysis of almost three dozen embryos in PLOS Genetics finds.