# Informatics

> **NIH NIH P01** · BAYLOR COLLEGE OF MEDICINE · 2021 · $107,727

## Abstract

PROJECT SUMMARY 
With the advance of genomic technologies including microarray and next generation sequencing (NGS) in 
recent years, a vast amount of genomic data has been generated. The quality control, statistical analysis and 
integration/interpretation of multi-dimensional large-scale data are facing new challenges. Bioinformatics, a 
interdisciplinary field that involves computer science, statistics and biology, is playing pivotal roles in genomic 
data analysis and integration in biomedical research. The major goals of Bioinformatics Core are 1) to promote 
the understanding the genomics and molecular mechanism of HIV-associated kidney diseases in human or 
mouse models and 2) to facilitate the interaction and data sharing among internal and external collaborators. 
To achieve these goals, we propose the following specific aims: 1) we will provide bioinformatic data analysis 
on high throughput deep-sequencing/microarray experiments to PPG projects ad statistical analysis to 
pathology and clinical core. We will be responsible for experimental design, data quality control, statistic and 
system biology analysis/interpretation of sequence data, transcriptomic and epigenomic profiles using next 
generation sequencing or microarray technologies; We will be fully engaged in each PPG project/research 
core that needs bioinformatics support and closely work with researchers and PI on any aspect related to 
bioinformatics/statistics. 2) We will implement a web-based data portal for data sharing among both internal 
and external investigators. We will develop a MIAME-compliant centralized database for storage of genomic 
and phenotypic/ pathological/clinical data from PPG project/core and a user-friendly interface for data query 
and online visualization; we will also integrate the data portal with LINCS-BD2K system for systematic data 
analysis to identify potential drug targets. 3) We will develop novel pipelines to facilitate analysis and 
integration of diverse genomic data from HIV virus and the host and meta-analysis of multiple datasets 
generated from PPG projects and relevant public datasets. We will identify meta signatures across multiple 
datasets and meta co-regulated network for better understanding of gene regulation associated with HIV- 
associated kidney diseases.

## Key facts

- **NIH application ID:** 10155091
- **Project number:** 5P01DK056492-21
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Weijia Zhang
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $107,727
- **Award type:** 5
- **Project period:** 1999-09-15 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10155091

## Citation

> US National Institutes of Health, RePORTER application 10155091, Informatics (5P01DK056492-21). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10155091. Licensed CC0.

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