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Open Source Fast Scalable Machine Learning API For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles...)

Home Page: http://h2o.ai

License: Apache License 2.0

Makefile 0.19% Groovy 0.03% Java 36.36% Shell 0.51% Python 19.48% Emacs Lisp 0.03% HTML 0.86% JavaScript 0.38% CSS 1.10% Ruby 0.02% R 10.09% Scala 0.14% Jupyter Notebook 26.99% TeX 2.57% Batchfile 0.06% Protocol Buffer 0.02% CoffeeScript 1.20%

h2o-3's Introduction

๐ŸŽ“ Ph.D., Computational RNA biologist at Harvard University, USA

I'm trying to understand the evolution and role of RNA and RNPs in biological systems using computational methods (machine learning, molecular dynamics, structure prediction) and experimental (yeast genetics) and codify this knowledge into predictive computational models that can be applied for future RNA therapeutics.

https://mmagnus.github.io

Key papers:

  • Rearrangements within the U6 snRNA core at the transition between the two catalytic steps of splicing with Konarska @IMOL, Poland, 2019
  • RNA 3D Structure Prediction Using Multiple Sequence Alignment Information with Das and Bujnicki @ Stanford University, USA & IIMCB, Poland, 2019
  • RNA-Puzzles toolkit: A computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools with the RNA-Puzzle Team @ IIMCB & IMOL, Poland, 2020 & the server https://rna-tools.online 2022
  • RNA 3D structure prediction using Deep learning, with Rivas, @Harvard, US, 2023-

RNA https://github.com/mmagnus?tab=repositories&q=rna&type=&language=&sort

Emacs https://github.com/mmagnus?tab=repositories&q=emacs&type=&language=&sort

See my projects @Github https://github.com/mmagnus?tab=repositories&q=&type=&language=&sort=stargazers

h2o-3's People

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