Galaxy-ML: An accessible,reproducible, and scalable machine learning toolkit for biomedicine

Supervised machine learning is an essential but difficult to use approach in biomedical data analysis. The Galaxy-ML toolkit (https://galaxyproject.org/community/machine-learning/) makes supervised machine learning more accessible to biomedical scientists by enabling them to perform end-to-end reproducible machine learning analyses at large scale using only a web browser. Galaxy-ML extends Galaxy (https://galaxyproject.org), a biomedical computational workbench used by tens of thousands of scientists across the world, with a suite of tools for all aspects of supervised machine learning.

This is a PLOS Computational Biology Software paper.

     

Two New Records of Genus Lepiota (Agaricaceae) from Pakistan

Biology Bulletin - In our ongoing efforts to inventory the lepiotaceous fungi of Pakistan, we here report on two species, new to Pakistan: Lepiota cingulum is also new to Asia, and L. oreadiformis....     

Exogenous Methyl Jasmonate Treatment Induces Defense Response Against Fusarium culmorum in Wheat Seedlings

Journal of Plant Growth Regulation - The Fusarium crown and root rot (FCRR) pathogen Fusarium culmorum (Fc) is a hemibiotrophic pathogen, with a short biotrophic phase preceding necrotropism....