Computational Analysis Core

计算分析核心

基本信息

批准号：
9350741
负责人：
DOUGLAS A LAUFFENBURGER
金额：
$ 26.11万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-07 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9350741
关键词：
Address Affect Algorithms Behavior Bioinformatics Biological Cell Count Cell Shape Cells Clinical Colonic Neoplasms Computer Analysis Computer Simulation Computing Methodologies Data Data Set Drug Controls Economic Inflation Ensure Event Experimental Designs Experimental Models Gene Expression Genes Genetic Transcription Goals Ligands Malignant Neoplasms Measurement Modeling Molecular Morphology Pharmaceutical Preparations Phenotype Population Process Quality Control Ribosomal RNA Sampling Signal Pathway Signal Transduction Testing Therapeutic Treatment Efficacy Ursidae Family Variant Work cancer cell cell type combinatorial cytokine design drug sensitivity experimental study extracellular insight interest leukemia member neoplastic cell novel pancreatic neoplasm power analysis prognostic receptor response success synergism therapy resistant transcriptome sequencing tumor tumor microenvironment

项目摘要

Core 2 – Project Summary The Computational Analysis Core (Core 2) will support Projects 1 & 2 by bringing necessary bioinformatics and computational methods to bear on the questions addressed by each project. More specifically, we will apply established computational pipelines to perform quality control on, and extract maximal information (cell types, states, circuits, and drivers) from, our rich data sets. We will help our CSBC team identify the cell types, states, and circuits active in the Leukemia and Colon and Pancreatic tumor models of Core 1 from the single- cell RNA-Seq data collected in Projects 1 & 2, as well as the molecular drivers of interesting behaviors. We will deploy numerical algorithms to uncover the predictive power of phenotypic measurements, alone or in combination, made via our Nanowell (NW) and Suspended Microchannel Resonator (SMR) platforms to explain cancer cell drug responses. When necessary, we will identify and/or develop new algorithms, enhancing our CSBC's quantitative and multivariate capabilities. Finally, we will work closely with our CSBC team members to help with experimental design, ensuring that an appropriate number of cells/samples are processed to test hypotheses of interest and that appropriate statistical testing is performed. By providing comprehensive analysis (QC, power, gene set enrichment) and modeling capabilities, we will dramatically enhance our ability to draw crucial insights from our data. This will lead to new hypotheses that can be tested by designing new experiments.

核心 2 – 项目摘要计算分析核心（核心 2）将通过引入必要的生物信息学来支持项目 1 和 2 更具体地说，我们将讨论每个项目所解决的问题的计算方法。应用计算建立的管道来执行质量控制，并提取最大信息（细胞我们将帮助我们的 CSBC 团队从我们丰富的数据集中识别细胞类型、状态、电路和驱动程序。核心 1 的白血病、结肠癌和胰腺肿瘤模型中的状态和电路活跃项目 1 和 2 中收集的细胞 RNA-Seq 数据，以及有趣行为的分子驱动因素。将部署数值算法来揭示表型测量的预测能力，单独或联合通过我们的 Nanowell (NW) 和悬浮微通道谐振器 (SMR) 平台进行组合，必要时解释癌细胞药物反应，我们将识别和/或开发新的算法，最后，我们将与CSBC密切合作。团队成员帮助进行实验设计，确保有适当数量的细胞/样本进行处理以测试感兴趣的假设并进行适当的统计测试。综合分析（QC、power、基因集富集）和建模能力，我们将极大地增强我们从数据中获取重要见解的能力，这将带来新的结果。可以通过设计新的实验来检验的假设。