MOMI Data Management

MOMI数据管理

• 批准号: 10420111
• 负责人: DOUGLAS A LAUFFENBURGER
• 金额: $ 47.08万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-19 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10420111
• 关键词: 2019-nCoV; Algorithms; Allografting; Anti-Inflammatory Agents; Atlases; Biological; Biology; COVID-19 pandemic; Categories; Chronology; Clinical; Cluster Analysis; Communicable Diseases; Complex; Computer Analysis; Computer Models; Consultations; Custom; Data; Data Analyses; Data Set; Development; Discipline; Disease; Engineering; Equilibrium; Etiology; Fetal Growth; Foundations; Global Awareness; Goals; Immune; Immune response; Immune system; Immunity; Immunologics; Immunology; Immunosuppression; Individual; Infection; Infertility; Inflammatory; Intervention; Intuition; Investigation; Lactation; Machine Learning; Maternal Health; Maternal-fetal medicine; Maternally-Acquired Immunity; Mathematical Biology; Mathematics; Measurement; Measures; Methods; Modeling; Nature; Newborn Infant; Organ; Pregnancy; Pregnancy Trimesters; Process; Property; Publications; Recording of previous events; Research Personnel; Sampling; Shapes; Statistical Data Interpretation; Supervision; System; Systems Biology; Techniques; Time; Vaccination; Vaccines; Woman; Work; base; cell type; computer framework; computer science; data management; differential expression; diverse data; fetal; heterogenous data; implantation; improved; in vivo; insight; maternal vaccination; multidisciplinary; multiple omics; neonatal health; novel; novel strategies; novel therapeutics; novel vaccines; operation; pathogen; predicting response; pregnant; programs; prophylactic; therapeutic vaccine; tool; vaccine platform; vaccine-induced immunity; vaccinology

Data Management and Analysis Core: Summary While previously regarded as a state of immunosuppression, emerging immunological studies conversely suggest that immune system shifts throughout pregnancy from inflammatory to anti-inflammatory, shifting to balance implantation and growth of the fetal allograft. Instead, OMIC level investigation has begun to point to an immunological clock that appears throughout pregnancy that may drive this balance between fetal-protection and maternal immunity- however the specific mechanisms that contribute to this biology and whether the same changes occur simultaneously throughout the immune system is incompletely understood. Thus, here we aim to develop an OMIC level data – integrating measures across the system and using vaccines as a mechanism to perturb the system in vivo. These datasets will be captured across gestation for the first time, building the foundational data to understand the immunological switches that occur throughout pregnancy to improve maternal health, develop novel strategies to treat infertility, to guide diseases requiring improved tolerance, as well as to improve neonatal health. In addition to assisting Project investigators with application of traditional systems biology mathematical tools, such as differential expression, enrichment, and clustering analysis, the Data Management and Analysis Core (DMAC) will develop and employ a spectrum of computational approaches arising from the realms of engineering and computer science, including machine learning techniques. We will emphasize modeling frameworks in which multiple features are used concomitantly for explanation or prediction of responses, as multi-variate correlates of protection. Moreover, these frameworks can examine how these multiple variables interact, offering potential advances in biological insights concerning mechanism. Both supervised and unsupervised classes of algorithms will be utilized, permitting two different perspectives on identifying correlates. The efforts of this Core will be intimately integrated into each of the experimental Projects.

数据管理和分析核心：总结