Upcoming Programs and Events

On Tuesday, December 12th (11 AM ET), IICD welcomes Yuqi Tan, PhD, Postdoctoral Fellow, Stanford University, School of Medicine. The seminar is hosted by Elham Azizi. The seminar will take place in person in Fairchild 1000 (Morningside Heights campus). If you wish to attend the seminar remotely, please register using the following link: https://columbiauniversity.zoom.us/meeting/register/tJ0td-yoqTwvHtONgFSuTf3GMYMvcmXpHLSk   Title: A Spatial Biologist's Guide to Decode Multiplexed Image Analysis Abstract: Over recent years, spatial omics has gained prominence as a leading-edge technology, illuminating the critical importance of spatial cell coordination in addressing multifaceted biological challenges, such as cancer prognosis, embryonic development, and the success of immunotherapy. There are two primary branches of spatial technology: one based on sequencing and the other on imaging. Notably, the latter imposes a substantial computational burden, necessitating users with extensive experience in machine learning and programming. As spatial technology becomes more accessible to a broader audience, it is imperative to equip scientists with basic bioinformatics training to harness the full potential of their datasets. Despite the emergence of various spatial analysis pipelines, many are tailored to specific data types. Few have addressed the intricacies of CODEX data as comprehensively as the Nolan lab, which pioneered CODEX in 2018. Over the years, we have optimized key aspects of CODEX analysis, focusing on three crucial aspects: 1) image segmentation, 2) quality assessment and normalization, and 3) spatial-resolved single-cell and tissue-level analysis. Drawing from our extensive experience and the latest computational tools, we introduce a user-friendly, end-to-end Python workflow for CODEX analysis. This workflow can be easily extended to other spatial multiplexed-image data, empowering researchers to unlock valuable insights from their own experiments. Bio: Yuqi Tan, a postdoctoral researcher at Stanford University, holds a BSc in Cell and Molecular Biology from the Chinese University of Hong Kong and a PhD in Computational Biology from Johns Hopkins University. With a record of 20 scholarships and awards, she specializes in crafting computational tools that integrate and transfer knowledge across various single-cell data modalities, whether in two or three dimensions. Her expertise finds practical applications in determining cell type identities and elucidating the spatial orchestration of cell types, especially within the domains of stem cell engineering, cancer immunotherapy, cancer initiation, and psychiatric diseases.   If you would like to meet one-on-one (possibility via zoom) or attend the lunch with the speaker, please contact the event organizer.  

Columbia Precision Medicine Joint Pilot Grants Program This funding opportunity is co-sponsored by the Precision Medicine Resource at the Irving Institute for Clinical and Translational Research, the Columbia Precision Medicine Initiative, and the Herbert Irving Comprehensive Cancer Center.   Overview This joint pilot award program funds one-year pilot studies in precision medicine. Studies must be relevant to advancing precision medicine basic science, pre-clinical/clinical approaches to tailor medical care (prevention, diagnosis, and/or treatment) to the individual patient, and/or precision cancer research.  Example areas include, but are not limited to: Genetic, genomic, or multi-omic data analyses, exposomics, biomarkers, genetic disease mechanism, stem cell biology, decision support tools, aggregated clinical/environmental data and/or patient-reported data to develop personalized medical care, new methods of working with precision medicine data and its integration with electronic health records, and new individualized approaches to effectively educate and communicate with patients.  Deadline: Tuesday, December 12, 2023  Award Duration: One (1) year  Award Amount: $100,000   Number of awards: Up to four per year 

Title: Robust Mendelian randomization coupled with Alphafold2 for drug target discovery Speaker: Zhonghua Liu, PhD Assistant Professor of Biostatistics in the Department of Biostatistics at Mailman School of Public Health, Columbia University Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to estimate the causal effect of a modifiable risk factor on the outcome of interest to remove unmeasured confounding bias. However, some genetic variants might be invalid IVs due to violations of core IV assumptions, for example, in the presence of population stratification and/or widespread horizontal pleiotropy. Inclusion of invalid genetic IVs for MR analysis might lead to biased causal effect estimate and misleading scientific conclusions. To address this challenge, we propose a novel MR method that first Selects valid genetic IVs and then performs Post-selection Inference (MR-SPI) based on two-sample genome-wide summary statistics. Extensive Monte Carlo simulation studies demonstrate the superior performance of MR-SPI. We apply MR-SPI to analyze 146 exposure-outcome pairs to establish putative causal relationships. We further analyze 912 plasma proteins using the large-scale UK Biobank proteomics data in 54,219 UK Biobank participants and identify 7 proteins significantly associated with the risk of Alzheimer's disease. We also apply AlphaFold2 to predict the three-dimensional (3D) structural alteration of these 7 proteins due to genetic variations. This event is hosted as part of the seminar series featuring leaders in precision medicine from across the nation. Co-presented by the Center for Precision Medicine and Genomics, the Columbia Precision Medicine Initiative, and the Precision Medicine Resource of the Irving Institute for Clinical and Translational Research. This event is supported in part by a gift from Pfizer to Columbia. Zoom and in-person. Please register to receive the Zoom information for this event.

The dual lives of pathogenic structures: from functional amyloids to domesticated capsids Luke Berchowitz, PhD Assistant Professor of Genetics and Development (in the Taub Institute for Research on Alzheimer's Disease and-the Aging Brain) Columbia University Medical Center