July 18 2022, We published our single-cell network biology analysis in PLoS Computational Biology. Congrats to Chirag! This work analyzes cell-type gene regulatory networks in human brains, repurposes drugs, and predicts phenotypic genes in Alzheimer’s Disease, a step to advance single-cell network medicine!
July 11-14 2022, we had our first in-person conference since the pandemic, ISMB 2022, locally in Madison! We presented posters and also learned great science.
June 3 2022, Saniya presented a poster in Computation and Informatics in Biology and Medicine Training Program and the Biomedical Data Science (BDS) PhD Program annual retreat.
May 31 2022, Congratulations to Ting as Highlighted Student in UW Genomics and Technology Newsletter.
May 24 2022, Noah and Sayali gave poster presentations in RECOMB 2022, San Diego, CA.
February 17 2022, UW News reports our recent manifold learning work for understanding how brain cells work.
January 31 2022, Our deepManReg is published in Nature Computational Science. Congratulations to Lab Alumni, Nam and Jiawei! This new method learns cross-modal manifolds as a feature graph for improving phenotype prediction and prioritizing multi-modal features & links. News & Views about this work is here.
November 19 2021, our manifold learning analysis to align multimodal data of neurons is published in Communications Biology. Congratulations to Jiawei and Jie!
November 12 2021, Congratulations to Saniya for passing her Ph.D. preliminary oral exam!
November 8 2021, Chirag presented a poster in the 50th Annual Meeting of Society for Neuroscience (Neuroscience 2021) on an integrative analysis for single cell network biology.
November 4 2021, Chenfeng presented a poster on manifold learning analysis of human brain and organoids in development, in 2021 Joint Annual Meeting of PsychENCODE, BICCN, Convergent Neuroscience and NCRCRG. Daifeng also presented a poster on manifold alignment of single cell multi-modal data, on behalf of Jiawei.
October 18 2021, Saniya presented a poster in ASHG 2021 on predicting gene regulatory networks linking risk variants to various clinical phenotypes in AD.
June 21 2021, Congratulations to Nam who successfully defended his PhD!
May 27 2021, scGRNom is published in Genome Medicine and Congratulations to Ting, Peter and Mufang! It was a great teamwork. scGRNom is a general-purpose computational pipeline to predict disease genes and regulatory networks from multi-omics data, especially at the cell-type level.
April 28 2021, Congratulations to Nam for being awarded the Ray and Stephanie Lane Fellowship from Department of Computational Biology in School of Computer Science at Carnegie Mellon University!
March 18 2021, Saniya won the Fan Favorite Award for her poster in 2021 Alzheimer’s Disease & Related Disorders Research Day.
March 18 2021, Congratulations to Saniya for being offered a predoctoral traineeship in the Computation and Informatics in Biology and Medicine (CIBM) program!
February 4 2021, Saniya presented an ISCB Student Council webinar on predicting regulatory mechanisms in Alzheimer’s disease progression.
November 16 2020, We present our recent work in the 13th annual RECOMB/ISCB Conference on Regulatory & Systems Genomics with DREAM Challenges! Nam gave an oral presentation on Varmole and Ting presented a poster on ECMarker. Exciting virtual experience this year!
November 9 2020, Saniya gave a poster presentation on her recent computational pipeline, ADSNPheno, to predict disease risk variants and gene regulatory mechanisms for the progression of Alzheimer’s disease in the first AAIC Neuroscience Next conference. Great job, Saniya!
November 6 2020, ECMarker is published in Bioinformatics and Congratulations to Ting and Nam! ECMarker is an interpretable machine learning model predicting clinical outcomes and simultaneously revealing molecular mechanisms in the development of human diseases.
October 8 2020, Varmole is out today in Bioinformatics and Congratulations to Nam and Ting! Varmole is an interpretable deep learning model to prioritize disease risk variants and genes via a biologically drop-connect technique. Also, it is scalable without needing prior feature selection and takes continuous input data.
September 29 2020, as UT alumni, Daifeng Wang and Shuang Liu are invited by Dr. Mia Markey to give a seminar on graduate professional development to graduate students of UT-Austin BME (Fall 2020 14200).
August 4 2020, our collaborative paper with Dr. Xinyu Zhao’s lab on the effects of running to adult neurogenesis was published in Cell Reports. Please see News.
June 12 2020, our integrative multi-omics analyses for identifying cell-type disease genes and regulatory networks in schizophrenia and Alzheimer’s disease has been submitted and is also available at Biorxiv. A great teamwork of Master’s student, Mufang Ying and senior undergraduate, Peter Rehani!
April 2 2020, Our multiview learning paper is published in PLoS Computational Biology and Congrats to Nam! We proposed a MV-ERM framework unifying various multiview learning approaches and also reviewed recent multiomic applications in different contexts (e.g., brain, cancer, single cell, bioenergy).
March 5 2020, Peter Rehani presented a poster on his joint work with Mufang Ying, “Computational Identification of Disease Genes at the Cellular Resolution for Alzheimer’s Disease and Schizophrenia” and won Best Undergraduate Student Poster in Alzheimer’s Disease and Related Disorders Research Day 2020, Madison, WI, USA
December 30 2019, ManiNetCluster is published in BMC Genomics! It was selected as one of Top 7 papers out of 105 submissions in ICIBM2019
July 1 2019, We moved to University of Wisconsin – Madison. Hello, Badgers!
June 9-11 2019, Nam won an NSF travel award and gave an oral presentation on multi-view learning for functional genomics in International Conference on Intelligent Biology and Medicine (ICIBM 2019), Columbus, OH, USA
May 4-9 2019, Ting attended RECOMB 2019 and worked as a student volunteer. Great experience!
March 23 2019, DaifengWang gave a talk on interpretable deep learning for understanding functional genomics in CSHL Network Biology 2019 at Cold Spring Harbor Laboratory, NY
December 14 2018, The PsychENCODE consortium publishes a series of papers in Science to reveal the functional genomics and molecular mechanisms of human brain development and mental illness. Daifeng Wang led one capstone paper using interpretable machine learning approaches to uncover functional genomics in the human brain. He also co-authored two others. See media reports including New York Times, NIH, Nature, ScienceNews,Scientific American, The Scientist, YaleNews.
December 11 2018, Daifeng Wang gave an oral presentation on functional genomics and integrative modeling for the human brain at the panel session of Larger-Scale Transcriptome and Epigenome Mappings, Modeling and Analyses in Developing and Diseased Human Brain in the annual meeting of American College of Neuropsychopharmacology (ACNP 2018) in Hollywood, FL, USA.
October 20 2018, Daifeng Wang gave a platform oral presentation on functional genomics in the human brain in American Society of Human Genetics Annual Meeting (ASHG 2018) in San Diego, CA, USA.
August 31 2018, Congratulations! Nam won the Best Poster Awardof 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) in Washington, D.C., USA. The poster title is “A Manifold Learning Based Approach to Reveal the Functional Linkages across Multiple Gene Networks: Nam Nguyen, Ian Blaby, Daifeng Wang“.
August 31 2018, Nam and Ting gave poster presentations on the 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) in Washington, D.C., USA
August 24 2018, Congratulations to Nam! He passed his Research Proficiency Examination.
Jun 11 2018, Daifeng Wang gave a selected abstract talk on comparative network analysis on epithelial to mesenchymal transition in lung cancer on International Conference on Intelligent Biology and Medicine (ICIBM 2018), Los Angeles, CA, USA
May 10 2018, Sanjeevani Choudhery gave a poster presentation on her Master’s research project, machine learning analysis reveals functional developmental and predictive gene modules associated with cortical thickness changes for Autism Spectrum Disorder (ASD) on 73rd Society of Biological Psychiatry Annual Meeting in New York City.
December 7 2017, our new paper, Comparative gene co-expression network analysis of epithelial to mesenchymal transition reveals lung cancer progression stages, is published in BMC Cancer.
Three high school students, Joshua Lee, VineetMalhotra, William Sun gain research experience in our lab from the summer program, Computer Scienceand Informatics Research Experience (CSIRE) for K-12 students, held from July 5 – Aug 4, 2017 (Stony Brook News and Vineet’s project demo).
June 13 2017, Daifeng Wang (SBU) and Ian Blaby (BNL) are awarded the 2017 SBU-BNL Seed Grant. The funded project is Large-Scale Comparative Regulatory Network Analysis in Photosynthetic Organisms.
May 30 2017, Daifeng Wang (Biomedical Informatics) and Flaminia Talos (Urology and Pathology) are awarded the interdisciplinary research pilot grant of Stony Brook Cancer Center, School of Medicine and College of Engineering and Applied Sciences. The funded project is Identification of gene regulatory networks for direct conversion of fibroblasts into bladder epithelia.
May 22-23 2017, Daifeng Wang received a travel fellowship to present a poster on gene regulatory network in the 2nd Penn Symposium on Mathematical & Computational Biology, Philadelphia, PA
April 18 2017, Alisha Kamat presented a poster on machine learning applications in lung cancer gene expression in 2017 Gloria and Mark Snyder Annual Symposium for Cancer Medicine, Stony Brook, NY
March 10 2017, Daifeng Wang gave an invited seminar in Biology Department of Brookhaven National Laboratory, Upton, NY
January 17 2017, Daifeng Wang presented an invited talk on internal and external gene regulatory networks in the systems genomics workshop of PAG XXV, San Diego, CA
November 30 2016, Daifeng Wang gave a poster presentation on internal and external gene expression dynamics in Computational Aspects of Biological Information (CABI) 2016 at Microsoft Research New England, Cambridge, MA
October 19 2016, the new paper, DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks, is published in PLoS Computational Biology
August 1 2016, Laboratory for Informatics, Networks and Systems (LINS) is established in Department of Biomedical Informatics, Stony Brook University.
July 8-12 2016, Daifeng Wang gave two oral presentations on systems genomics and academic social networks in 2016 Intelligent Systems for Molecular Biology (ISMB), Orlando, Florida, USA. ISMB is the flagship annual conference of the International Society for Computational Biology.