The Michigan Institute for Data Science (MIDAS) catalyzes data science at the University of Michigan through support for faculty, research, education and training, and industry engagement.

WHAT’S NEW

3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification

| Research | No Comments
Title 3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification Published in Scientific Reports 8, October 2018 DOI 10.1038/s41598-018-33574-w Authors Alexandr A. Kalinin, Ari Allyn-Feuer, Alex Ade, Gordon-Victor Fon,…

The effectiveness of parking policies to reduce parking demand pressure and car use

| Research | No Comments
This study is a part of the "Reinventing Transportation and Urban Mobility" project, funded by the Michigan Institute for Data Science. Title The effectiveness of parking policies to reduce parking demand…

VIPER: variability-preserving imputation for accurate gene expression recovery in single-cell RNA sequencing studies

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This research was supported by funding from the Michigan Center for Single-Cell Genomic Data Analytics—a part of the Michigan Institute for Data Science. Title VIPER: variability-preserving imputation for accurate gene…

TAIJI: Approaching Experimental Replicates-Level Accuracy for Drug Synergy Prediction

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MIDAS-affiliated researchers recently published a paper on accurate and fast computational tools for predicting drug synergistic effects. Title TAIJI: Approaching Experimental Replicates-Level Accuracy for Drug Synergy Prediction Published in Bioinformatics, November…

Most CSCAR workshops will be free for the U-M community starting in January 2019

| Educational, General Interest, Happenings, News | No Comments
Beginning in January of 2019, most of CSCAR’s workshops will be offered free of charge to UM students, faculty, and staff. CSCAR is able to do this thanks to funding…

Eric Michielssen completes term as Associate Vice President for Research – Advanced Research Computing

| General Interest, Happenings, News | No Comments
Eric Michielssen will step down from his position as Associate Vice President for Research - Advanced Research Computing on December 31, 2018, after serving in that leadership role for almost…

U-M approves new graduate certificate in computational neuroscience

| Educational, General Interest, Happenings, News | No Comments
The new Graduate Certificate in Computational Neuroscience will help bridge the gap between experimentally focused studies and quantitative modeling and analysis, giving graduate students a chance to broaden their skill…

ARC Director Sharon Broude Geva elected Chair of the Coalition for Academic Scientific Computation

| HPC, News | No Comments
Dr. Sharon Broude Geva, Director of Advanced Research Computing at the University of Michigan, has been elected Chair of the Coalition for Academic Scientific Computation (CASC) for 2019. Founded in…

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MIDAS Highlights

MIDAS Year in Review

Read about the progress MIDAS has made in the past year in catalyzing data science at U-M through support for faculty, research, education and training, and industry engagement. View on the web, or download PDF.

MIDAS working groups foster cross-disciplinary collaboration

MIDAS regularly convenes research working groups, bringing together investigators from various fields to work on shared research issues or pending funding opportunities. Subjects include Data Integration, Mobile Sensor Analytics, Teaching Data Science, Trustworthy Data Science. For more information or to suggest a topic for a new group, contact Jing Liu, MIDAS Senior Scientist (ljing@umich.edu; 734-764-2750).

Data Science for Music

The Data Science for Music Challenge Initiative distributed four, one-year  grants of $75,000 each for research projects at the intersection of music and data science.

Women in Big Data at Michigan

The event highlighted women data science researchers at U-M, and provided resources and support for women pursuing careers in data science. The keynote talk was given by Xihong Lin, Henry Pickering Walcott Professor of Biostatistics at the Harvard H.J. Chan School of Public Health.

Data Acquisition for Data Science

Data Acquisition for Data Science (DADS) supports acquisition, preparation, management, and maintenance of specialized research data sets used in current and future data science-enabled research projects across U-M, with special focus on the four challenge initiative areas pursued by MIDAS: transportation science, health science, social science, and learning analytics.