# Bioinformatics Core

> **NIH NIH U54** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2021 · $78,475

## Abstract

Abstract 
The Bioinformatics Core (CORE B) will interface with each projects, cores, and UTSW consortium to provide (i) 
centralized bioinformatics and biostatistical support; (ii) centralized database; (iii) integrative data analysis across 
different platforms; and (iv) analytical and methodical reports for preparation of manuscripts. Core B Leader, Dr. 
Wang, and Co-Leader, Dr. Baladandayuthapani, have been working closely and synergistically for several 
years with core and projects leaders and co-leaders, and are capable of supporting study designs, data analysis, 
and management of data resources of the entire PDTC program. Core B will use robust IT structure and an 
extensive computing environment that includes Windows, Unix/Linux, Mac OS X, and two quad-processor Sun 
SPARC SMP systems. In addition, Core B will rely on two primary institutional computing resources, an HPC 
cluster of 336 compute nodes (each node with 32GB RAM; 1.3 GB RAM per core) with dual, 12-core Opteron 
processors (8,064 CPUs total), and an Itanium-2 SMP compute server with 32CPUs and 128GB RAM. The core 
Leader and Co-Leader have built various pipelines for sequencing data and protein expression data processing 
and analysis, which will be applied to analyze data. Standard design principles and statistical algorithms will be 
used and new methods will be developed as needed. These include: a) Parametric and nonparametric methods 
for estimation and hypothesis testing; b) Linear models and generalized additive models to find the best models 
that fit complex data structures; c) Kaplan-Meier method to estimate the distributions of time-to-event outcomes; 
d) Log-rank test to compare the distributions among different PDX groups; and e) Proportional hazards models 
to test for PDXs treatment with single drugs and combinations. Drs. Wang and Baladandayuthapani will work 
closely with UTPDTC investigators to facilitate hypothesis testing across projects by integrating datasets from 
multiple laboratories using various algorithms, including principal components, partial least squares, and 
Bayesian network-based models. Data analyses will be performed using R and Bioconductor packages. The 
Core will document all the analyses and produce HTML or PDF reports (using R packages: Sweave, knitR, and 
R markdown).

## Key facts

- **NIH application ID:** 10242647
- **Project number:** 5U54CA224065-04
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Jing Wang
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $78,475
- **Award type:** 5
- **Project period:** 2017-09-30 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10242647

## Citation

> US National Institutes of Health, RePORTER application 10242647, Bioinformatics Core (5U54CA224065-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10242647. Licensed CC0.

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