# CSHL Programming for Biology Course

> **NIH NIH R25** · COLD SPRING HARBOR LABORATORY · 2020 · $91,092

## Abstract

ABSTRACT
PROGRAMMING FOR BIOLOGY
 2020 – 2024
The goal of the Cold Spring Harbor Laboratory Course in Programming for Biology is to
provide biologists with the advanced knowledge and programming tools they need to
deal with the genomic information explosion. Complementary to training in web tools
such as BLAST, this course teaches researchers how to manage, analyze and display
large data sets by creating dedicated programs that combine existing and custom tools
and platforms. This 16 day course begins with an intensive training in Python
programming, including object-oriented programming and the BioPython library. The
second week introduces essential bioinformatics analysis tools and methods, each
accompanied by appropriate programming exercises. We emphasize the design and
implementation of complex analysis pipelines that directly address a biologist's research
questions using practical software engineering and scientific computing methods. The
course combines formal lectures with extensive hands-on laboratories in which students
solve a series of computational problem sets drawn from common scenarios in biology
research and data management. In a three-day final project that solidifies the course's
teachings, students pose real-life problems using their own data and work in groups with
faculty to solve them.

## Key facts

- **NIH application ID:** 10021913
- **Project number:** 2R25HG007825-07
- **Recipient organization:** COLD SPRING HARBOR LABORATORY
- **Principal Investigator:** DAVID J. STEWART
- **Activity code:** R25 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $91,092
- **Award type:** 2
- **Project period:** 2014-09-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10021913

## Citation

> US National Institutes of Health, RePORTER application 10021913, CSHL Programming for Biology Course (2R25HG007825-07). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10021913. Licensed CC0.

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