Section: Research

Postdoctoral Position Available

Lab Page Link

Zhiping Weng, Ph.D.

Academic Role: Professor

Faculty Appointment(s) In:
   Biochemistry and Molecular Pharmacology
   Program in Bioinformatics & Integrative Biology

Other Affiliation(s):
   Interdisciplinary Graduate Program

Bioinformatics and Computational Genomics

We focus our research on regulatory molecules and their interactions, such as regulatory proteins and their DNA/RNA target sites, small silencing RNAs and their RNA targets, and protein-protein interaction. Our lab has three main projects:

• Gene Regulation

We aim to develop computational methods for understanding the molecular mechanism of gene regulation. We develop novel ways to discover transcription factor binding sites in genomic DNA. Because the sequences of these sites are of low information content, we pursue multiple approaches, including better characterizing transcriptional start sites and alternative proximal promoters, detecting clusters of transcription factor binding sites using probabilistic models, and identifying genes that are co-regulated and taking advantage of the enrichment of the sequence motifs in their promoters. We take an integrative approach using extensive high-throughput genomic and epigenomic data, such as chromatin-immunoprecipitation of transcription factors, nucleosome positioning, histone modifications, DNA methylation, and DNA replication.

• Protein Docking

We develop methods to compute binding affinities between protein molecules. Combining this ability with a fast Fourier transform-based search algorithm, we develop computational methods for predicting protein-complex structures. We take a multiple-stage approach, i.e., we develop an initial stage algorithm ZDOCK to perform an exhaustive search in the translational and rotational space, and subsequent refinement algorithms such as ZRANK for structure refinement and reranking. We participate in the community-wide blind test of protein docking algorithms CAPRI.

• Small Silencing RNAs

We develop computational methods to understand the biogenesis and regulatory mechanisms of small silencing RNAs (microRNAs or miRNAs, small silencing RNAs or siRNAs, and PIWI-interacting RNAs or piRNAs). We build computational pipelines to analyze high-throughput sequencing data of small silencing RNAs. We map tens of millions of sequence reads to the genome, quantify their length and nucleotide properties, genomic localization, relative abundance in different cell types and/or genotypes, evolutionary conservation, and discover any other features that can uncover the biogenesis and target recognition of the small silencing RNAs.

Office: LRB 1010
Phone: 508-856-8866
Fax: 508-856-2392
E-mail: Zhiping.Weng@umassmed.edu
Keywords: Systems Biology, Genomics, Bioinformatics, Gene Expression, Gene Regulation

More on Zhiping Weng's Research Research | Publications | Rotations | Biography View All Sections on One Page

Postdoctoral Position Available Please contact Dr. Weng directly for more information regarding this post-doctoral position. Postdoc Position in Comparative Genomics The laboratories of Profs. Zhiping Weng (Bioinformatics) and Bob Brown (Neurology) at University of Massachusetts Medical School (UMMS) invite applications for a postdoc position in comparative genomics. In an NIH-funded project undertaken jointly with Dr. David Goldstein (Director, Center for Human Genome Variation, Institute for Genome Sciences & Policy, Duke University), the Brown lab will perform whole genome sequencing with the Solexa platform on 40 amyotrophic lateral sclerosis (ALS) patients. The postdoc will develop and apply computational tools to analyze this wealth of sequence data and identify genetic variations among the individuals and prioritize them with other functional data, such as those generated with the HapMap and ENCODE projects. Subsequently, the Brown lab will genotype the prioritized variations in cohorts of 1,000 cases and 1,000 controls, and the postdoc will participate in the analysis of the resulting data to discover determinants of susceptibility and phenotype. An ideal candidate would have a PhD in computational biology, bioinformatics, computer science, or another quantitative field and have substantial experience in analyzing high-throughput genomics data. Excellent programming skills and statistics knowledge are essential. UMMS is a highly collaborative research environment and Profs. Weng and Brown have recently been recruited to UMMS to establish the Program in Bioinformatics and Integrative Biology and neurogenetics research in the Neurology Department. The collaboration between the two labs will lead to many future projects in comparative genomics and its application to human diseases.