# Computational approaches for protein functional analysis using CRISPR screens

> **NIH NIH R35** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2020 · $405,000

## Abstract

Abstract
 The development of a high-throughput biotechnology highly relies on relevant computational methods for
systematic optimization and data analysis. On the other hand, the development of bioinformatics methods
requires in-depth understanding of the biological systems and the experimental protocols. The long-term goal
of our lab is to develop computational methods that can be seamlessly integrated with high-throughput
experiments to address biological questions, with a focus on transcriptional and epigenetic regulations.
 Understanding protein functions is a fundamental aim in biology. The recent advances of CRISPR screening
techniques have enabled functional studies of proteins in a high-throughput manner, leading to novel discoveries
beyond the capacity of traditional methods. During the next five years, our short-term goal is to develop
solutions to boost the utilization of high-throughput CRISPR screens for protein functional analysis. To achieve
this goal, we propose three research topics:
 1) Prediction of sgRNA knockout effects for improved sgRNA library design in CRSIPR screens. This will
 address the bioinformatics needs in the design of CRISPR screens;
 2) Protein domain analysis using CRISPR tiling-sgRNA screens. This will lead to innovative solutions for the
 studies of protein domain and structure.
 3) Inference of transcriptional regulatory networks from CRISPR screen and -omic data. This will lead to the
 development of new methodology to address an open problem involving protein-protein interactions and
 regulations of transcription factors and epigenetic regulators.
 Collectively, the proposed project will contribute new methods to enrich the toolbox for protein functional
analysis, and will provide novel insights into the fields of transcriptional and epigenetic regulations.

## Key facts

- **NIH application ID:** 10027200
- **Project number:** 1R35GM137927-01
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Han Xu
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $405,000
- **Award type:** 1
- **Project period:** 2020-09-15 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10027200

## Citation

> US National Institutes of Health, RePORTER application 10027200, Computational approaches for protein functional analysis using CRISPR screens (1R35GM137927-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10027200. Licensed CC0.

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