Natural Selection Has Differentiated the Progesterone Receptor among Human Populations. Chen Eitan. Both bioinformatics and … Tel: 415-502-2572 There are 3,100+ professionals named "Jingjing - Jessie Li", who use LinkedIn to … University of California, San Francisco. University of California, San Francisco. UCSD Profiles is managed by the UC San Diego Altman Clinical and Translational Research Institute (ACTRI). To request changes to a department listing please open a ticket at help.ucsf.edu, or contact the IT Service Desk at (415) 514-4100. A deep learning framework identifies pathogenic noncoding somatic mutations from personal prostate cancer genomes. The scope of this informal forum is geared toward work in basic science: lab bench and computation. Email: jingjing.li@ ucsf.edu Address: 35 Medical Center Way, RMB 934H, San Francisco, CA 94143. Jingting Li's profile, publications, research topics, and co-authors. Because many complex human diseases have a strong genetic component, it has been long anticipated that once we can sequence one’s personal genome, we would be able to predict the person’s clinical outcome. Therefore, although most somatic mutations are localized in the noncoding cancer … We perform ChIP-Seq and ATAC-Seq in iPSC-derived cells to delineate the genome-wide chromatin architecture in disease-related cell types, and build machine learning algorithms to identify non-coding mutations (SVs, indels and CNVs) that disrupt local and global chromatin architecture. Because these approaches allow large-scale and quantitative analyses of biological phenomena and data obtained from many disciplines, they can ask questions and achieve unique insights not imaginable before the genomic era. Li , J. et al. American Journal of Human Genetics (AJHG) 2018,103:1-13. affecting ~18% in African Americans, 6% in East Asians, and ~10% on average across the nation. Li J, Pan C, Zhang S, Spin JM, Deng A, Leung LLK, Dalman RL, Tsao PS, Snyder M Natural Selection Has Differentiated the Progesterone Receptor among Human Populations. Cell 2018, 174: 1361-1372. Our research aims to build a data-driven framework to quantitatively define health. We use genomic approaches to identify genetic elements in spontaneous preterm birth, and analyze their population differentiation. Li J, Pan C, Zhang S, Spin JM, Deng A, Leung LLK, Dalman RL, Tsao PS, Snyder M, Li J, Hong X, Mesiano S, Muglia LJ, Wang X, Snyder M, Stevenson DK, Shaw GM, Li J, Shi M, Ma Z, Zhao S, Euskirchen G, Ziskin J, Urban A, Hallmayer J, Snyder M, ©2021 The Regents of the University of California, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, Bakar Computational Health Sciences Institute (BCHSI), Parker Institute for Cancer Immunotherapy. Altmetrics Details PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. Gene-environment interaction in the era of precision medicine. Click on a faculty name to view a detailed description of an individual research program, contact information, recent publications and links to other relevant websites. Molecular Systems Biology 2014, 10:774. View Jingjing Li’s full profile. We use multi-omics approaches to delineate the convergent molecular networks in neurological diseases, and develop deep learning frameworks to directly predict clinical outcomes from personal genomes. Li, J. et al. Decoding the genomics of abdominal aortic aneurysm. Core. Speaker: Jingjing Li, PhD, Assistant Professor of Neurology, UCSF Weill Institute for Neurosciences The Basic Research Monthly Meeting focused on prostate... 12:30pm Virtual Event Trends in Genetics 2013, 29(2): 116-124. Fetal de novo mutations and preterm birth. Jingjing Li, PhD researches large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. 2The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, The Parker Institute for Cancer Immunotherapy, The Bakar Computational Health Sciences Institute, Department of Neurology, School of Medicine, University of California, San Francisco, San Francisco, California. Cell Systems 2015, 1(5): 361-374. This condition has a strong genetic component, and is hallmarked by a strong population disparity, e.g. Li, J. et al. All of the faculty associated with the BMS graduate program are listed below. Weizmann Institute of Science - Department of Molecular Genetics. Emmy (Jingjing) Li Graduate Student at UCSF Boston, Massachusetts 36 connections. Speaker: Jingjing Li, PhD, Assistant Professor of Neurology, UCSF Weill Institute for Neurosciences The Basic Research Monthly Meeting focused on prostate cancer research across UCSF. Weizmann Institute of Science - Department of Molecular Genetics. October 17, 2019 By Karen. All of the faculty associated with the BMS graduate program are listed below. Li, J. et al. There are 3,500+ professionals named "Jingjing Li", who use LinkedIn to exchange information, ideas, and opportunities. Natural selection has differentiated the progesterone receptor among human populations. Eran Hornstein. jingjing.li@ucsf.edu. We develop machine learning algorithms to define personal genome baselines for disease occurrences, and identify actionable lifestyle elements whose modification could compensate for genetic risk. Chao Li, Shuo Wang, Jiun-Lin Yan, Rory J Piper, Hongxiang Liu, Turid Torheim, Hyunjin Kim, Jingjing Zou, Natalie R Boonzaier, Rohitashwa Sinha, Tomasz Matys, Florian Markowetz, Stephen J Price. Li, J. et al. By continuing we assume you accept the use of cookies. We integrate personal genome baselines and individual lifestyles for precision health management. These cohort-based approaches cannot directly identify individual pathogenic noncoding mutations from personal cancer genomes. We recently showed that these seemingly heterogeneous mutations are in fact convergent onto common pathways. With comprehensively profiled individual lifestyles and physiologies, we aim to extend the classical P=G+E model to a Bayesian framework, where we stratify individuals based on personal genome baselines, followed by identifying lifestyle elements whose modification could improve clinical outcome. microRNA regulatory variation in human evolution. Preterm birth affects 15 million pregnancies worldwide every year, and is the leading cause for neonatal morbidity and mortality. @ Eli and Edythe Broad Center of Regeneration, Building Data-Driven Frameworks to Solve Complex Diseases, Personal Genomes + Clinical Records + Individual Lifestyles + Emerging Technologies. Our current understanding of disease genomes is largely limited to coding sequences, and the non-coding regions, accounting for ~98.5% of the human genome, have been largely unexplored for their contribution to disease etiologies. Exploiting the determinants of stochastic gene expression in S. cerevisiae for genome-wide prediction of expression noise. Report this profile; Experience. We also actively work on congenital heart diseases for a direct translation from genome sequences to clinical manifestations. (Note that publications are often cited in additional ways that are not shown here.) Cell 2019, 177(1):38-44. Health is a descriptive concept, which is often defined as “free from disease”. Primary Thematic Area: Cell 2019, 177(1):38-44. Large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, health records, and digitized clinical traits from imaging and wearable sensor readouts. In addition to our clinical research, we have keen interests in many fundamental questions in genome sciences. We previously demonstrated the RNA binding specificity of human Argonaute proteins, and are now elucidating the mutational effects on RNA secondary structure and protein-RNA interaction. At UCSF, his research is focused on cancer genomics. This site is running Profiles RNS version v2.12.0-792-gbe55c6ce on PROFILES-PWEB01. We use these technologies to derive quantitative traits for fine-mapping of genetic elements. Each genomic locus has its own evolutionary trajectory, and we trace the evolutionary origin of disease-associated mutations back to archaic humans, primates, as well as distantly related vertebrate species. In addition to using clinical records to model gene-environment interaction, we also leverage imaging and wearable sensor technologies to longitudinally digitize clinical traits. PLoS Genetics 2017 13(4): e1006689. Assistant Professor, Neurology. Identifying mRNA sequence elements for target recognition by human Argonaute proteins. We also perform digital signal processing to analyze these longitudinal data to capture subtle signals that will enable us to detect diseases before symptoms emerge. Jingjing Li, PhD From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases. Jingjing Li, PhD. We build machine learning models to define personal genome baselines for the risk of cardiovascular diseases, and quantify the contribution from lifestyle adjustments to risk reduction. Integrated systems analysis reveals a molecular network underlying autism spectrum disorders. It's free! Li, J. et al. Jingjing Li , PhD Jingjing Li, PhD Integrating genomic information, health records and socioeconomic data, we aim to solve the stark health disparity problem , and achieve precision management for human pregnancies. Our understanding of noncoding mutations in cancer genomes has been derived primarily from mutational recurrence analysis by aggregating clinical samples on a large scale. Assistant Professor We use cookies to ensure a smooth browsing experience. American journal of … Wang, C. and Li, J. Exome sequencing of neonatal blood spots identifies genes implicated in bronchopulmonary dysplasia. 139 connections. Large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, health records, and digitized clinical traits from imaging and wearable sensor readouts. Decoding the Genomics of Abdominal Aortic Aneurysm. Research summary: Large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. Jingjing Li. Gene-environment interaction in the era of precision medicine. 33. Gene-Environment Interaction in the Era of Precision Medicine. Jingjing Li @ UCSF Big Data for Precision Medicine. Deepak Lamba, PhD. His research direction involves integrating the genomic and clinical big data in cancer research using machine learning approaches. We combine genomic analysis and iPSC techniques to model the mutational impacts on disease onset and progression. American Journal of Respiratory and Critical Care Medicine (AJRCCM) 2015, 192:589-596 (the Blue Journal). UCSF Profiles is managed by the UCSF Clinical and Translational Science Institute (CTSI), part of the Clinical and Translational Science Award program funded by the National Center for Advancing Translational Sciences (Grant Number UL1 TR000004) at the National Institutes of Health (NIH). The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. This concept has been the cornerstone of today’s precision medicine. This site is running Profiles RNS version v2.12.0-792-gbe55c6ce on PROFILES-PWEB01. We are particularly interested in understanding the evolutionary trade-offs associated with local adaptation events during modern human evolution and migration, and these evolutionary "costs" will help us understand the origin of human diseases. University of California, San Francisco. Low perfusion compartments in glioblastoma quantified by advanced magnetic resonance imaging and correlated with patient survival. View the profiles of professionals named "Jingjing - Jessie Li" on LinkedIn. Identification of human neuronal protein complexes reveals biochemical activities and convergent mechanisms of action in autism spectrum disorders. Experience. Integrated systems analysis reveals a molecular network underlying autism spectrum disorders. Jingjing Li Assistant Professor at UCSF San Francisco Bay Area 148 connections. PNAS 2010, 107(23): 10472-10477. The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. Li, J. et al. We therefore use multi-omic profiling strategies to construct biological networks, and map genomic mutations onto biological networks to identify disease-associated pathways. Jingjing Li, PhD From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases. Contact Us. The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. Li, J. et al. Jingjing Li: Mon, Wed, Fri, 2-4p: details BMS 270/BMI 219: Fundamentals of Microbiome Research: Peter Turnbaugh: Mon-Fri, 2:00-4:00p (5/17-5/28) details: BMS 270: Current Approaches to Quantitative Proteomics in Biology: Arun Wiita: Mon, Wed, Fri, 9:30a-12p: details: BMS 270: Advanced Topics on Unlocking Human Autoimmunity: Mark Anderson We study the structural organization of genes on biological networks, and use ChIP-Seq to delineate the epigenome landscapes of the developing brain and heart in humans. The candidates will also develop close collaborations with both UCSF and Stanford research groups including many leading scientists, ... CV, a short summary of your qualifications and research interests, and contact information for three references to Dr. Jingjing Li. Using iPSC-derived cells to identify pathogenic non-coding mutations Jingjing Li, PhD From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases. He did his postdoc research at Stanford Genetics as a Banting Fellow, and later received … Cheng received Ph.D. from the National University of Singapore working on elucidating the regulation of pre-mRNA splicing in breast cancers. Jingjing Li Assistant Professor at UCSF Mountain View, California Higher Education. Daniel Lim, MD, PhD studies the role of chromatin remodeling factors in the regulation of neural stem cell fate. Dr. Li’s predoctoral training was in engineering and machine learning, and later received his PhD in Molecular Genetics from the University of Toronto. However, our genomic analysis of complex diseases is often challenged by mutational heterogeneity, where different patients often carry different sets of clinical mutations. Li, J. et al. Large-scale analysis of disease genomes Integrating genomic data and digitized physiological and behavioral profiles, we aim to detect diseases before symptoms emerge. View the profiles of professionals named "Jingjing Li" on LinkedIn. Molecular mechanisms and novel therapeutic targets for retinal degenerations. Join to Connect. Join to Connect. Jingjing Li. Jingjing Li, PhD From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. Address: 35 Medical Center Way, RMB 934H, San Francisco, CA 94143. The fields of bioinformatics and computational biology at UCSF aim to investigate questions about biological composition, structure, function, and evolution of molecules, cells, tissues, and organisms using mathematics, informatics, statistics, and computer science. View the profiles of professionals named "Jingjing - Jessie Li" on LinkedIn. Clinical phenotyping using emerging technologies University of California, San Francisco (UCSF) - Department of Neurology. We use multi-omics approaches to delineate the convergent molecular networks in neurological diseases, and develop deep learning frameworks to directly predict clinical outcomes from personal genomes. Read our theory paper: Gene-environment interaction in the era of precision medicine. Li, J., et al. University of California, San Francisco. University of California, San Francisco (UCSF) - Department of Neurology. Cancer Research 2020, 80:4644–54.. 32. Click on a faculty name to view a detailed description of an individual research program, contact information, recent publications and links to other relevant websites. We also investigate many understudied areas in genomic medicine, with a focus on genomic alterations at the RNA level. Genome Research 2014, 24(5):775-785. Jingjing Li's profile, publications, research topics, and co-authors. jingjing.li@ucsf.edu. 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