@Cobanoglu_Lab

UTSW Distinguished Fellow. We think drug discovery is a machine learning problem. Pauca sed matura is a guiding philosophy.

 Dallas, TX
utsouthwestern.edu/labs/cobanoglu/
Joined April 2018
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  • Following68
  • Followers130
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Cancer drug discovery should be solved as a low rank tensor completion problem: biorxiv.org/cgi/content/shor… We describe constructing, using and completing such a tensor; provide true positive and true negative validations. Thanks to team, incl.: @vasanth1786 @didemagac @gr8straj
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Murat Can Çobanoğlu retweeted
PLOS Comp Biol@PLOSCompBiol28 Jul 2022
Have cell types for your single cell data but your visualization doesn't know about them? Check out Haisu. It makes your favorite visualizer (t-SNE, UMAP, & PHATE) label-aware. It also supports hierarchical labels (T cell --> CD8 T cell). @Cobanoglu_Lab plos.io/3b9Ydah

Haisu: Hierarchically supervised nonlinear dimensionality reduction

Author summary Information collection and representation is critical in modern applications as advances in technology alleviate storage and computational processing constraints. Large quantities of...

journals.plos.org
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Murat Can Çobanoğlu retweeted
Kemal Oflazer@oflazer12 Jun 2021
Carnegie Mellon Üniversitesi Mezunlar Derneği Türkiye olarak 19 Haziran 2021 Cumartesi, Türkiye saati ile 16-19 arasında (9am-11am EDT) CMU'lu arkadaşlarımız ile yapay zeka üzerinde konuşacağız. Herkesi davet ediyoruz. Kayıt Linki: us06web.zoom.us/webinar/regi…
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Philippe Roudot@PhilippeRoudot21 Apr 2021
Another open #PHDPosition in #ComputerVision for #CellBiology. We are looking for an enthusiastic student to push the envelope in the analysis of molecular dynamics across scales and automate navigation in 5D datasets. Info at bit.ly/3eih8NC. Deadline June 30th!
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Predictive engine built using, including but not limited to: python, pandas, numpy, scipy, statsmodels, RDKit, TensorFlow, Tensorly. Web interface built using nginx, flask, jinja2, Tabulator. Our code for both parts will also shortly be made available as open source.
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Finally, I'd like to thank my chair @gdanuser1 and my institution @UTSWNews for all the support I've received during the years it took to realize this project. I hope this tool facilitates cancer drug discovery worldwide. Feel free to reach out with any questions or comments!
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Just listened to @jack on NYT The Daily. One comment stuck: algorithms should be explainable. I think we lack metrics that reward transparency. ML methods (incl in biology) shouldn't compete purely on accuracy, but also on interpretability. Explainable 98% accuracy vs opaque 99%?
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Our new paper just appeared online: doi.org/10.1093/bioinformati… Resolving overlap is important for accurate TF activity inference.
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Looking forward to talking at Acıbadem tomorrow!
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James Allison's Nobel prize led us to Stockholm, and the fantastic celebrations here. It is a great joy to attend the events here with my gorgeous fiancee @didemagac ! – at Stockholm, Sweden
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Demo of our team's deep learning in VR hackathon project—aka deVoReaNN: youtu.be/E_VWewj_jX8 Repo: github.com/NCBI-Hackathons/d… Awesome team; awesome hackathon! :)
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We built a VR environment for developing deep learning models. Awesome team! @mcdannunzio @siddhxagarwal Meyer Zinn, Kevin Van Horn, Xiaoxian Jing Fantastic hackathon here at UT Southwestern #uhackmed
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Our team is awesome! Not that I'm biased or anything :)
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What if there was a "#scientist passport" issued by the #UnitedNations, that was granted to every bona fide scientist working in an accredited institution? We'd possibly save so much energy, time & money that's currently lost applying for visas, tracking immigration laws etc.
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How about a VR environment for deep learning model development? Think of moving layers around by hand, connecting them by grabbing and pulling 'cords' etc. For images, one can watch the intermediate layers during learning with the simple gesture of grabbing them and pulling them.
40%Great idea!
20%Good for beginners
40%Gimmick
5 votes • Final results
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We launched an exciting new project: @FiolkaLab and we @Cobanoglu_Lab will develop an active machine learning guided microscope. @gr8straj will provide tumor models, Hu Zhao will clear them, and Satwik Rajaram will analyze the output. Result: 3D insights from tumor microenv.
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Proud to welcome our two new lab members for the summer: Alex George and Reed Zimmermann. Alex will develop generative probabilistic scRNAseq analysis software. Reed will use URSM to bridge bulk & scRNAseq to look for metabolic markers in melanoma microenv.
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2018 marks the 75th anniversary of UT Southwestern Medical Center, our distinguished institution with a strong legacy. Proud to call UTSW home. 75.utsouthwestern.edu
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