# Project-002

> **NIH NIH U41** · ROSWELL PARK CANCER INSTITUTE CORP · 2020 · $448,603

## Abstract

Bioconductor is a successful project for the analysis and comprehension of high-throughput data. A key
component of this success is the development of innovative statistical algorithms relevant to leading-edge
bioinformatic data types. This proposal focuses on three aspects of algorithm development, to enable
continued success of the project. The first aim is (1) to implement methodological and data structure support
for signal recovery and inference across modern genomic assays. Signal recovery and inference are
fundamental steps in the transformation of raw data into meaning summaries. The second aim is (2) to develop
annotation and workflow support for genome biology and genomic medicine. This recognizes the importance of
associating statistical insight with biological meaning. The final aim is (3) to provide the necessary
infrastructure to support scalable computational analysis of genome-scale data. A key idea emerging from this
work is the STAMP (scan, transform, amalgamate, model, pack) pattern for genomic analysis.

## Key facts

- **NIH application ID:** 9922972
- **Project number:** 5U41HG004059-16
- **Recipient organization:** ROSWELL PARK CANCER INSTITUTE CORP
- **Principal Investigator:** Martin T Morgan
- **Activity code:** U41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $448,603
- **Award type:** 5
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9922972

## Citation

> US National Institutes of Health, RePORTER application 9922972, Project-002 (5U41HG004059-16). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/9922972. Licensed CC0.

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