A5061993781- Tissue Engineering and Regenerative Medicine
- Cancer Cells and Metastasis
- Epigenetics and DNA Methylation
- Bioinformatics and Genomic Networks
- Cancer Genomics and Diagnostics
- Genetics, Bioinformatics, and Biomedical Research
- Advances in Oncology and Radiotherapy
- Ethics in Clinical Research
- Artificial Intelligence in Healthcare
- Science, Research, and Medicine
- Economic and Financial Impacts of Cancer
- Multiple and Secondary Primary Cancers
- Molecular Biology Techniques and Applications
- Health Systems, Economic Evaluations, Quality of Life
- Scientific Computing and Data Management
- Research Data Management Practices
- Biomedical Ethics and Regulation
- Biomedical Text Mining and Ontologies
- CRISPR and Genetic Engineering
- Cancer, Hypoxia, and Metabolism
- RNA modifications and cancer
- BRCA gene mutations in cancer
- Radiomics and Machine Learning in Medical Imaging
- Genomics and Rare Diseases
- AI in cancer detection
Center for Information Technology
2024
National Cancer Institute
2018-2024
National Institutes of Health
2022
Scripps Research Institute
2016
University of California, San Diego
2011
Rockefeller University
2011
University of Hawaiʻi at Mānoa
2011
University of Hawaii System
2011
Abstract To metastasize, carcinoma cells must attenuate cell–cell adhesion to disseminate into distant organs. A group of transcription factors, including Twist1, Snail1, Snail2, ZEB1, and ZEB2, have been shown induce epithelial mesenchymal transition (EMT), thus promoting tumor dissemination. However, it is unknown whether these factors function independently or coordinately activate the EMT program. Here we report that direct induction Snail2 essential for Twist1 EMT. knockdown completely...
The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical genomic data through both harmonized aggregation federated approaches. decreasing cost sequencing (along with other genome-wide molecular assays) increasing evidence its utility will soon drive generation sequence from tens millions humans, levels diversity. In this perspective, we present GA4GH strategies addressing major challenges revolution. We...
Abstract Since 2014, the NCI has launched a series of data commons as part Cancer Research Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical to support cancer research promote sharing NCI-funded studies. This review describes each (Genomic Commons, Proteomic Integrated Canine Service, Imaging Clinical Translational Commons), including their unique shared features, accomplishments, challenges. Also discussed is how CRDC implement Findable, Accessible,...
Abstract More than ever, scientific progress in cancer research hinges on our ability to combine datasets and extract meaningful interpretations better understand diseases ultimately inform the development of treatments diagnostic tools. To enable successful sharing use big data, NCI developed Cancer Research Data Commons (CRDC), providing access a large, comprehensive, expanding collection data. The CRDC is cloud-based data science infrastructure that eliminates need for researchers...
Proteomics has emerged as a powerful tool for studying cancer biology, developing diagnostics, and therapies. With the continuous improvement widespread availability of high-throughput proteomic technologies, generation large-scale data become more common in research, there is growing need resources that support sharing integration multi-omics datasets. Such datasets require extensive metadata including clinical, biospecimen, experimental workflow annotations are crucial interpretation...
<div>Abstract<p>Since 2014, the NCI has launched a series of data commons as part Cancer Research Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical to support cancer research promote sharing NCI-funded studies. This review describes each (Genomic Commons, Proteomic Integrated Canine Service, Imaging Clinical Translational Commons), including their unique shared features, accomplishments, challenges. Also discussed is how CRDC implement Findable,...
<p>CRDC Dataset Citations by Year</p>
<p>CRDC Program Collaborators</p>
<div>Abstract<p>More than ever, scientific progress in cancer research hinges on our ability to combine datasets and extract meaningful interpretations better understand diseases ultimately inform the development of treatments diagnostic tools. To enable successful sharing use big data, NCI developed Cancer Research Data Commons (CRDC), providing access a large, comprehensive, expanding collection data. The CRDC is cloud-based data science infrastructure that eliminates need for...
<p>CRDC Program Collaborators</p>
<p>Cancer Research Data Commons (CRDC) displaying each component of the CRDC infrastructure.</p>
<p>CRDC Program Collaborator</p>
<div>Abstract<p>More than ever, scientific progress in cancer research hinges on our ability to combine datasets and extract meaningful interpretations better understand diseases ultimately inform the development of treatments diagnostic tools. To enable successful sharing use big data, NCI developed Cancer Research Data Commons (CRDC), providing access a large, comprehensive, expanding collection data. The CRDC is cloud-based data science infrastructure that eliminates need for...
<p>CRDC Dataset Citations by Year</p>
<div>Abstract<p>Since 2014, the NCI has launched a series of data commons as part Cancer Research Data Commons (CRDC) ecosystem housing genomic, proteomic, imaging, and clinical to support cancer research promote sharing NCI-funded studies. This review describes each (Genomic Commons, Proteomic Integrated Canine Service, Imaging Clinical Translational Commons), including their unique shared features, accomplishments, challenges. Also discussed is how CRDC implement Findable,...
<p>Cancer Research Data Commons (CRDC) displaying each component of the CRDC infrastructure.</p>
<p>CRDC Program Collaborator</p>
<p>PDC study summary page offering a comprehensive overview of both data and metadata.</p>
<p>Available data types in the proteomic commons</p>
<p>Cross referencing to genomic and imaging resources for individual cases. Example of cross-referencing (<b>A</b>) on the Clinical tab PDC’s Explore page; <b>B,</b> External References section PDC study summary pages.</p>
<p>Cross referencing to genomic and imaging resources for individual cases. Example of cross-referencing (<b>A</b>) on the Clinical tab PDC’s Explore page; <b>B,</b> External References section PDC study summary pages.</p>