# Cross Training Core

> **NIH NIH U54** · UNIVERSITY OF MARYLAND BALTIMORE · 2024 · $179,444

## Abstract

The Cross-Training Core (CTC) for the U54 ROBIN OligoMET Center will consist of experienced faculty
members of the Division of Computational and Systems Biology (CSP) in the Department of Pathology and
Laboratory Medicine of Weill Cornell Medical College (WCM). The team at WCM will work in close collaboration
with teams at the other Institutions, and a history of collaboration already exists between the CTC team members
and the investigators leading the Research Projects and the other Research Cores, which will further ensure the
successful progression of the Center. The CTC activities will be centered around the following purposes: Aim 1)
To provide a unified analytical framework across the U54 ROBIN OligoMET Center to foster cross-project data
integration and comparison. Imaging, omics, and radiomics data are found in a variety of forms (e.g., different
platforms, file formats, etc.), and training people on how to manage each of these instances is challenging and
inefficient. We will have unified analytical framework within the U54 ROBIN OligoMET Center where data is
aggregated and standardized, greatly decreases the training complexity and increases reproducibility which
results in a more fluid training process. Aim 2) To provide educational support and training across the U54 ROBIN
OligoMET Center. Advances in genomics, transcriptomics, metabolomics, and radiomics technologies have led
to exponential rises in both production and availability of multimodal data. In light of these rapid evolutions,
disseminating the latest bioinformatics methods within the U54 Center – and the broader biomedical community
– is a challenge of paramount importance. The CTC will address such challenge by creating an open educational
platform that will provide a rich interactive learning environment, leveraging a cloud-based framework to
collaboratively create and share tutorials and learning experiences. To this end, the CTC will build upon a 10-
year experience in the computational genomics and data science domains and training biologists and clinicians
in computational methods. Aim 3) To develop novel analytical approaches for the comprehensive
characterization of oligometastatic prostate cancer (PCa) via integrated analyses of multimodal big data. Omics
and radiomics technologies, multiparametric in situ imaging, and spatially-resolved molecular and image
analyses are rapidly evolving fields. Therefore, continually evolving technologies, software, algorithms, and
analytical methods are efforts of essence. PCa investigations across the U54 ROBIN OligoMET Center
encompass a multitude of these domains, hence it is of paramount importance that a versatile and innovative
portfolio of approaches is developed to fully support the ongoing and future research. The U54 ROBIN OligoMET
Center will therefore provide an ideal platform for such cross-disciplinary training, and the CTC will support such
crucial endeavor through developing and disseminating ad-hoc training modu...

## Key facts

- **NIH application ID:** 10910086
- **Project number:** 5U54CA273956-03
- **Recipient organization:** UNIVERSITY OF MARYLAND BALTIMORE
- **Principal Investigator:** Luigi Marchionni
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $179,444
- **Award type:** 5
- **Project period:** 2022-08-04 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10910086

## Citation

> US National Institutes of Health, RePORTER application 10910086, Cross Training Core (5U54CA273956-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10910086. Licensed CC0.

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