Li Lab

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Research Information Our lab is focused on the design and application of statistical and computational algorithms to elucidate global transcription regulatory mechanism. An elaborate system of transcription regulation is responsible for the morphological and behavioral complexity in higher eukaryotes. This regulatory system consists of diverse trans-acting protein factors and cis-acting regulatory DNA sequences. Recently, Chromatin ImmunoPrecipitation coupled with whole genome tiled microarray (ChIP-chip) and/or next-generation sequencing (Solexa, SOLid and 454) has evolved as a powerful and unbiased technique to study genome-wide in vivo binding of the trans-acting protein factors. The application of this technology to multiple factors and/or in multiple conditions allows biologists to study how trans-factors differentially regulate transcription in a combinatorial manner. However, it also poses great challenges for the development of effective algorithms, the key link between massive raw data and biological hypotheses. We developed a series of algorithms to reliably detect and annotate ChIP-enriched regions using Affymetrix whole-genome tiling arrays, including 1) Model-based Analysis of Tiling-arrays (MAT; PNAS 2006) for ChIP-region detection, 2) extreme MApping of OligoNucleotide (xMAN, BMC Genomics 2007) for microarray probe mapping, 3) Cis-regulatory Element Annotation System (CEAS; NAR 2006) for ChIP-region annotation. Since the inception in early 2006, they have been adopted by hundreds of academic users and are now considered as the ChIP-chip data analysis standard in many labs. We are also working with the ENCODE spike-in consortium, which consists of more than 10 transcriptional regulation groups worldwide, to systematically analyze the performance variability introduced in ChIP-chip protocols, array platforms, and analysis methods. We are also in close collaboration with several labs on identifying global regulation targets of a series of key transcription factors, including estrogen receptor (Cell 2005; Nature Genetics 2006); androgen receptor (Molecular Cell 2007); STAT5 (J. Biological Chemistry 2006); TAL1 (Blood 2006); and p53 (Bioinformatics 2005).

Announcements Open Positions (New, September 2007): Postdoctoral Fellowship: Two post-doctoral fellowships in bioinformatics are available immediately to work in the laboratory of Dr. Peter Park at Harvard Medical School. This is a new posting; previously advertised positions have been filled. The long-term goal of the group is to understand gene regulation through computational analysis of genomic data. In each position, the successful candidate will have a fantastic opportunity to work on new data sets, from the Cancer Genome Atlas project and the ENCODE project. The first position requires integrating data from multiple microarray platforms; experience in microarray analysis is required and some knowledge in cancer biology is a plus. The second position involves analysis of epigenomics data to understand how chromatin modification affects gene regulation. Ideal candidates will have a Ph.D. in a quantitative field and have a substantial experience in bioinformatics. Excellent programming skills are essential and previous experience with R is a plus. Those who have applied previously are welcomed to apply again; due to the number of indiscriminant applications, those from abroad may not be acknowledged. The Harvard Medical area is one of the most exciting places in the world for biomedical research and there is ample opportunity for collaborative work with top biologists. Please send your CV, a brief statement of research interests, pdfs of your three best papers, and contact information for three references to peter_park[at]harvard[dot]edu. Graduate Students There are multiple openings for graduate students to work on the problems described above. The focus of the work will be computational; but, if desired, the student will have ample opportunity to carry out wet-lab work in one of the collaborating laboratories. Those with interest in epigenetics are particularly welcomed. Scientific Programmer: Applications are invited for a position in software development. A bachelor's degree in computer science or a related field is required. The primary object is to design web-based software that implement algorithms developed by the members of the group. Experience in web programming (CGI, Perl, mysql, etc) and familiarity with various platforms would be ideal. The individual will have a chance to develop important tools that enable medical researchers to interpret their genomic datasets. The person will be funded by the National Center for Biomedical Computing grant recently awarded at Harvard.