Kalin Nonchev (@nonchevk) 's Twitter Profile
Kalin Nonchev

@nonchevk

PhD at @ETH Zurich, machine learning and biomedical data

ID: 1501628621299097602

linkhttps://kalinnonchev.github.io calendar_today09-03-2022 18:39:03

43 Tweet

69 Followers

157 Following

Aayush Grover (@aayushgrover8) 's Twitter Profile Photo

We just released Hi-C predictions for 157 ENCODE ATAC-seq cell lines and primary cells, made using our model UniversalEPI 🎉 From ATAC-seq to genome architecture, no Hi-C experiment required! Super excited to see these tracks now live on the UCSC Genome Browser! Start exploring👇

Gunnar Rätsch (@gxr) 's Twitter Profile Photo

I'm looking forward to help shape and participate in this InnoSuisse AI Oncology initiative under the leadership of the EPFL AI Center and ETH AI Center. We aim to bring AI methodology closer to the clinical practice. ETH AI Center EPFL_AI_Center linkedin.com/posts/epfl-ai-…

Eric and Wendy Schmidt Center (@schmidt_center) 's Twitter Profile Photo

Top Performers: 🏆 Kalin Nonchev – 1st Crunch 1, 2nd Crunch 2 (ETH Zurich) 🏆 Manfred Seiwald – 2nd Crunch 1 (University of Salzburg) 🏆 Team PathBio – 3rd Crunch 1 – Sen Yang (Stanford University), Jinxi Xiang (Stanford), Wei Yuan (Sichuan University), Yijiang Chen (Stanford), Xiyue Wang (Stanford)

Gunnar Rätsch (@gxr) 's Twitter Profile Photo

Thanks for organizing! Such challenges are very important to have in order to distill whats "good sales" and whats good "performance". However, most performance measures have limitations & the real test is to use the method for scientific discovery or translational applications.

bioRxiv Bioinfo (@biorxiv_bioinfo) 's Twitter Profile Photo

DeepSpot2Cell: Predicting Virtual Single-Cell Spatial Transcriptomics from H&E images using Spot-Level Supervision biorxiv.org/content/10.110… #biorxiv_bioinfo

Karsten Borgwardt (@kmborgwardt) 's Twitter Profile Photo

Several postdoc positions and positions for scientific software engineers will become available in my department at the Max Planck Institute of Biochemistry in Munich over coming months. Topics include machine learning in bioengineering, in proteomics and in medicine. 1/2

Andre Kahles (@akkah21@genomic.social) (@akkah21) 's Twitter Profile Photo

After years of research and continuous refinement, we’re thrilled to share that our paper on the MetaGraph framework — enabling Petabase-scale search across sequencing data — has been published today in Nature (nature.com/articles/s4158…).

CrunchDAO đź§  (@crunchdao) 's Twitter Profile Photo

Nearly 1,000 researchers from 62 countries took part, proving that open collaboration can push biomedical discovery faster than any single lab. Read the full article 🔗ericandwendyschmidtcenter.org/updates/machin…