# Applied Bioinformatics Laboratory

> **NIH NIH P30** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $75,270

## Abstract

PROJECT SUMMARY/ABSTRACT
The Applied Bioinformatics Laboratories Shared Resource (ABL) provides cost-efficient, state-of-the-art,
and cutting-edge computational analysis and support for biomedical data, including, but not limited to, multi-
omics, imaging, and clinical data to Perlmutter Cancer Center (PCC) members and their collaborators. ABL is
essential to the research of the four PCC Research Programs, as data analysis is central to most modern cancer
research. During the funding period, we nearly doubled our clientele, co-authored 71 peer-reviewed manuscripts
(21 with impact factor >20) and were contributed to 43 funded grants with PCC investigators in cancer genetics,
epigenetics, and machine learning. ABL is directed by Aristotelis Tsirigos, PhD, Professor of Pathology and
Medicine. He has >18 years of experience in genomics and machine learning and has co-authored >130 studies
in peer-reviewed journals, including high-impact studies in cancer genomics, epigenomics, high-throughput
single-cell transcriptomics, and cancer diagnostics using machine learning. The ABL mission is to accelerate
scientific discovery through expert experimental design, robust data quality assessment, comprehensive
computational analyses, and integration of multi-modal biomedical datasets to provide insight into biological
function and mechanism. This goal is accomplished by using a variety of established and novel computational
workflows, methods, and tools. ABL contributes to all aspects of the research cycle, from the generation of ideas
and preliminary data for grant applications to analysis, interpretation, and management of data for manuscripts.
ABL integrates closely with, and has developed computational expertise to process data generated by, several
other PCC Shared Resources (SRs). We provide start-to-finish standardization of the analysis of sequencing
datasets, rigorous data quality assessment, integration, and visualization, as well as statistical expertise in
collaboration with the Biostatistics Shared Resource. The results of analyses conducted in ABL are shared with
investigators via a web interface and are accessible via the High-Performance Computing (HPC) cluster. Like
other SRs, ABL is overseen by the Division for Advanced Research Technologies, and PCC member satisfaction
with our services is assessed via regular surveys and an advisory board. The aims of ABL are: 1) to provide
streamlined analyses of biomedical data generated by PCC investigators in a timely, cost-effective manner, 2)
to manage and disseminate data and results of bioinformatics analyses, and 3) to educate and inform members
of the PCC community on bioinformatics and machine learning methodologies and their use in cancer research.

## Key facts

- **NIH application ID:** 10769326
- **Project number:** 2P30CA016087-43
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Aristotelis Tsirigos
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $75,270
- **Award type:** 2
- **Project period:** 1996-12-01 → 2029-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10769326

## Citation

> US National Institutes of Health, RePORTER application 10769326, Applied Bioinformatics Laboratory (2P30CA016087-43). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10769326. Licensed CC0.

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