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DahShu's virtual journal club is held monthly to promote the most cutting edge research in the fields of data sciences. Click to download presentation slides and seminar recording materials for each event.

Chair and Associate Chairs

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Rui (Sammi) Tang

Chair

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Jiarui Zhang

Associate Chair

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Jing Lu

Associate Chair

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Upcoming events

    • Fri, March 29, 2024
    • 09:00 - 10:00
    • https://us02web.zoom.us/j/88216435588?pwd=NFR0WHo0ME5YTTREeGhZMGZCdXZtdz09
    Register

    Fri, Mar 29, 2024, 09:00 – 10:00AM (PDT), 12:00 – 1:00PM (EST)

    Abstract

    Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly.


    On Mar 29 2024, Dr. Tao Wang will introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. He will highlight spacia’s power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. In his preprint, the team evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. Spacia was deployed in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors.


    Dr Wang’s work demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. The team also revealed differential spatial interaction patterns between γδ T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.



    Speaker:


    Dr. Tao Wang runs a top computational immunology lab in UT Southwestern Medical Center. Statistics, informatics, medicine, and biology are the four integral pillars of Dr. Wang’s interdisciplinary research program. He has been working on mining public and in-house high throughput data to achieve a deeper understanding of the mechanisms of various human diseases, with a heavy emphasis on immunological diseases, and their diagnosis, prognosis, and treatment. Examples of Dr. Wang’s achievements include: (1) he created the pMTnet model for predicting the pairing between TCRs and T cell epitopes (Nature Machine Intelligence, 2021). (2) He is the first investigator to develop methodologies to integrate single T/B cell gene expression with TCR/BCR-sequencing data (publications in Nature Methods and Nature Machine Intelligence). (3) Dr. Wang developed advanced methodologies to study immune epitopes. He developed BepiTBR for accurate prediction of B cell epitopes (iScience, 2022). He developed a statistical methodology to consider the clonality structures of tumor neoantigens, which led to improved prognostic and predictive powers for cancer patients (Science Immunology, 2020). (4) He developed novel bioinformatics tools for analyses of spatial transcriptomics data (Nature Methods, 2022)



    Strategic Alliance:


Past events

Fri, January 26, 2024 Large-scale pancreatic cancer detection via non-contrast CT and deep learning
Fri, December 01, 2023 Explainable AI: Model-Agnostic Interpretability in Machine Learning
Fri, October 13, 2023 Generative AI for Healthcare and Life Sciences on AWS
Fri, September 29, 2023 NAIR Software: Unlocking the Immune System's Secrets by Network Analysis and Advanced Machine Learning
Fri, August 18, 2023 Sequential Decision Making with Uncertainty: Contextual Bandits as a Missing Data Problem
Fri, July 07, 2023 The landscape of tolerated genetic variation in humans and primates
Fri, April 28, 2023 Does Real-World Evidence have a role in Precision Oncology?
Fri, January 27, 2023 Veridical data science with a case study to seek genetic drivers of a heart disease
Fri, November 11, 2022 Genes, Brain, and Us
Fri, October 14, 2022 Clinical and Analytical Validation of Companion Diagnostic Devices and Their Applications in Personalized Medicine
Fri, July 15, 2022 Medical AI
Fri, June 24, 2022 Machine Learning for Evidence Generation from Real World Longitudinal Patient Electronic Health Records
Fri, April 29, 2022 Increasing the reproducibility and rigor of single-cell RNA-seq through the use of statistics and data science
Fri, February 25, 2022 Drug Discovery in the Era of Precision Medicine
Fri, January 21, 2022 Statistical analysis of single-cell RNA-seq data with multiple samples
Fri, November 19, 2021 Fusing multi-modal patient data for machine learning in cardiovascular disease
Fri, September 17, 2021 Single arm trials with a synthetic control arm built from RWD
Fri, August 20, 2021 In Search of Effective and Reproducible Clinical Imaging Biomarkers for Population Health and Oncology Applications of Screening, Diagnosis and Prognosis
Fri, June 25, 2021 The New FIRRMA Regulations and Their Impact on Biotechnology and Life Science Industries
Mon, May 24, 2021 Automated Image Labeling for Medical Imaging AI
Fri, April 23, 2021 Dynamic Data Monitoring of Ongoing Clinical Trials
Fri, March 19, 2021 IP Legal Considerations for Precision Medicine and Digital Health Companies
Fri, February 19, 2021 Machine Learning Based Integrative Multi-Omics Analysis— Presented by Global Champion of All Three PrecisionFDA AI Challenges
Fri, January 29, 2021 How to quantify and interpret the treatment effects for comparative clinical studies of COVID-19 diseases?
Fri, November 13, 2020 Telehealth and Other Advancements in Healthcare Technology Spurred by COVID-19
Fri, October 02, 2020 A New Measurements-Based Approach to Machine Learning for Bioinformatics
Fri, September 25, 2020 Under the hood of 1Point3Acres COVID-19 map & tracker
Fri, August 28, 2020 Demystifying the drop-outs in single cell RNA-seq data
Fri, July 17, 2020 Using multiple natural experimental designs to triangulate the impact of a policy change
Fri, May 29, 2020 How AI is changing the financial service industry
Fri, March 13, 2020 AI Drug Discovery and Repurposing
Fri, February 28, 2020 The i3+3 Design: A Rule-Based Dose-Finding Approach for Phase I Trials
Fri, December 13, 2019 Statistical Considerations in the Clinical Development of Novel Cancer Therapies
Fri, November 15, 2019 15 Tips on Making Better Use of R Markdown
Wed, October 02, 2019 Principles of Data Science
Fri, September 20, 2019 AI Derived Personalized Solution: The Key Driver in the Era of Digital Health
Fri, August 09, 2019 Scalable Automatic Machine Learning with H2O
Fri, June 07, 2019 Network Meta-Analysis for Decision-Making
Fri, May 03, 2019 Global Prediction of Gene Regulatory Landscape Using Bulk and Single-Cell RNA-seq
Fri, March 08, 2019 Innovative adaptive design for immune-oncology trials
Fri, February 22, 2019 Survival analysis methods for non-proportional hazards
Tue, January 08, 2019 Design of Dose-Response Clinical Trials
Fri, November 16, 2018 Neyman-Pearson Classification Algorithms and NP Receiver Operating Characteristics
Fri, October 19, 2018 Machine Learning in Medical Imaging: the Challenge and Opportunity in Drug Development and Precision Medicine
Fri, September 14, 2018 Disease Heritability Inferred from Familial Relationships Reported in Medical Records
Fri, July 20, 2018 Big Data and Artificial Intelligence in Healthcare
Fri, May 25, 2018 The Genomic Landscape and Pharmacogenomic Interactions of Clock Genes in Cancer Chronotherapy.
Mon, May 21, 2018 Estimation of Treatment Effect under Non-Proportional Hazards
Mon, May 21, 2018 Subgroup Identification in Drug Development: Are Post-Selection Adjustments of Efficacy Useful?
Mon, April 30, 2018 An accurate and robust imputation method scImpute for single-cell RNA-seq data
Fri, March 30, 2018 Genome-scale signatures of gene interaction from compound screens predict clinical efficacy of targeted cancer therapies.
Thu, February 22, 2018 Expression Recovery in Single Cell RNA Sequencing
Wed, January 31, 2018 Single-cell transcriptomics reconstructs fate conversion from fibroblast to cardiomyocyte
Thu, October 19, 2017 Statistical Challenges in Immuno-Oncology, a Cellular Therapies Perspective
Tue, September 26, 2017 Big-Data Analysis Points Toward a New Cancer Therapeutic Discovery Approach
Thu, September 14, 2017 Software Patenting: The Current State of the Law
Mon, August 21, 2017 The Asthma Mobile Health Study, a Large Scale Clinical Study Using ResearchKit

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@Dahshu 2020

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