Computational Tools for Proteomics

National Heart, Lung, And Blood Institute

Investigators

Linked publications, trials & patents

Abstract

The Knepper laboratory studies the molecular mechanisms of water transport in the renal collecting duct and the pathophysiology of water balance disorders. The studies employ multi-omic methods including those involving protein mass spectrometry and various next generation sequencing (NGS) modalities. ----- Proteomics tools. Mass spectrometers suitable for protein mass spectrometry are rapidly improving in performance capabilities, providing more and more data for systems biology-oriented studies. However, quite often, data processing tasks are rate limiting for progress in proteomics-based studies. In this project, we are developing software tools needed for interpretation of the large data sets obtained. These tools are developed initially for our own studies but we make them available to other investigators at https://esbl.nhlbi.nih.gov/Bioinformatic%20Tools.htm. ---- NGS data integration. The identification of putative enhancers involved in transcriptional regulation of Aqp2 gene transcription and other key genes important to kidney water transport is an important objective of the laboratory. They can be identified through a combination of ATAC-seq data, histone H3K27 acetylation ChIP-seq data, and RNA-polymerase II ChIP-seq data. To integrate such data sets to make the most precise identification of enhancers, we have developed NGS-Integrator, which employs Bayesian integration techniques. ---- Big Data integration of multi-omic data sets. To integrate multiple -omic data sets to addressed focused questions, we have developed Bayesian integration approaches. --- Systems biology based investigation often requires the design and production of new antibodies. We have developed software to predict the optimal synthetic peptide sequences for production of antibodies (see https://esbl.nhlbi.nih.gov/AbDesigner/). ---- To aid in dissemination of our software, the algorithms are coded in Java, which is platform-independent, allowing the code to run on a variety of machines. In addition, where possible, we are striving to make software available online for execution (see https://esbl.nhlbi.nih.gov/Bioinformatic%20Tools.htm).