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Our paper – “ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data” – has been selected as the Frontiers in Neuroinformatics Editor’s Pick 2021.

This paper is one of the best 23 papers that have been selected out of more than 700 papers – over the past two years. These papers are cited based on strong contribution to theory, and methodology, and studies that have been most impactful. This collection aims to further support Frontiers’ strong community by recognizing highly deserving authors.

Editor Collection 2021 can be accessed using this link:  https://www.frontiersin.org/research-topics/21206/frontiers-in-neuroinformatics-editors-pick-2021#articles

Our paper can be accessed using this link: https://www.frontiersin.org/articles/10.3389/fninf.2019.00070/full

Our paper entitled “High performance computing framework for tera-scale database search of mass spectrometry data” has now accepted and have appeared in Nature Computational Science (Link: https://rdcu.be/cvFan). In this paper we developed a novel high performance techniques that allows analysis of proteomics data for tera-scale (and beyond) databases using large supercomputers.

Our paper can be accessed at this link: https://www.nature.com/articles/s43588-021-00113-z

Homepage for HiCOPS (the hpc framework described above): https://hicops.github.io/