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Single-Cell & Computational Biology Core

单细胞

基本信息

批准号：
10688118
负责人：
Kivanc Birsoy
金额：
$ 39.38万
依托单位：
ROCKEFELLER UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-23 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10688118
关键词：
Algorithms Binding Bioinformatics Biological Biology Breast Cancer Model Breast cancer metastasis Cell Communication Cells Cellular biology Chromatin Clinical Colorectal Cancer Computational Biology Computational algorithm Computing Methodologies DNA Data Data Set Disease Distal Elements Fire - disasters Gene Expression Gene Expression Profiling Generations Genes Genetic Transcription Glean Interruption Malignant Neoplasms Metabolic Metabolite Interaction Metastatic to Methodology Methods Modeling Molecular Neoplasm Metastasis Organ Pathway Analysis Pathway interactions Phenotype Primary Neoplasm Proteomics RNA RNA-Binding Proteins Regulatory Element Regulon Reporter Research Personnel Series Site System Systems Biology Universities cancer cell cell type colorectal cancer metastasis empowerment experimental study gene network innovation insight mRNA sequencing malignant breast neoplasm metabolic abnormality assessment metabolomics metastasis prevention novel pharmacologic prevent programs ribosome profiling single cell sequencing sound technology development therapeutic target transcription factor transcriptome transcriptomics

项目摘要

SUMMARY The Single-Cell Sequencing and Computational Biology Core B will be the central hub for devising and implementing all Single-Cell Sequencing experiments, as well as the application of powerful computational algorithms to such data as well as other bulk mRNA sequencing and metabolomic data to generate integrated models of gene networks and regulatory factors underlying metastatic progression. All three Center Projects will approach metastasis systematically, relying on the generation of transcriptomic, ribosomal profiling, single-cell sequencing, proteomic, metabolomic and chromatic accessibility data. As such, this Center will rely heavily on rigorous and statistically sound Computational Biology and Bioinformatics approaches pioneered by Saeed Tavazoie, a leader in Systems Biology, who will be a co-leader of this Core. Similarly, all three Projects will extensively employ Single-Cell Sequencing methods to define and characterize cell-cell interactions and cellular gene expression states within metastatic tumors and to develop novel single-cell methods. Junyue Cao, a leader in Single-Cell Sequencing technology development and application will be a co-leader of this Core. The combined Systems-level focus of these investigators applied to the multi-layered data generated from distinct stages of metastatic progression will enable the establishment of an unprecedented integrated Systems-level model of breast and colorectal cancer metastasis—providing the framework for further mechanistic studies that will refine this model, ultimately revealing critical nodes that when interrupted genetically or pharmacologically will prevent and eradicate metastatic disease. Computational methods that will be foremost applied to the problem of metastatic progression include: 1. iPAGE: an information-theoretic Pathway Analysis of Gene Expression algorithm that allows the systematic discovery of pathways that are differentially modulated across transcriptomes of any cell-types. 2. FIRE: an information-theoretic algorithm that identifies local DNA and RNA elements that underlie gene expression changes, uncovering associated transcription factors and RNA-binding proteins that govern such programs. 3. TEISER: an algorithm that discovers RNA regulatory elements from transcriptomes, enabling identification of their trans-binding factors. 4. An algorithm that integrates transcriptomic and phenotypic features (such as survival) from large-scale cancer compendia to implicate critical clinically-associated genes.

总结