News

With 11 publications and being the nominee from the PSC department as an outstanding student, Naveen has been awarded 2022-23 Outstanding Doctoral Student Researcher for the College of Agriculture and Applied Sciences (CAAS). This is a very competitive reward and he competed among all the applicants from the other departments in CAAS.

Miss Simardeep Kaur is a Nehru Doctoral Fulbright fellow at KAABiL Laboratory, USU. Her doctoral thesis focuses on deciphering the microRNA related modulations in contrasting rice genotypes under drought stress. As a Fulbright fellow she will be learning bioinformatic tools and softwares for comprehensive analysis of the data generated from her molecular biology related work from wet-lab experiments. She will be improving her skills to handle larger data set like those for methylome, transcriptome, lncRNAs, miRNAs, validation techniques and their analysis so that she can integrate molecular biology with bioinformatics to develop the drought tolerant agricultural crops.

Raghav Kataria is a PhD student in the KAABiL lab. He is currently working on pathogen-host protein-protein interactions using computational tools and various molecular biology techniques in his research in bioinformatics. Raghav was recently awarded the "Campbell Scientific Graduate Fellowship", which is provided by "Apogee Instruments".

Andrew is a computer science student and software developer. He currently works on developing a method to create datasets for deep learning image recognition tasks, enabling robots to generate their own training data.

David is a CS PhD student from Colombia. He worked full-time as a full-stack software developer for 6 years while finishing his bachelor's degree in Software and Computer Engineering and got a MSc. degree in Computational Biology.

ProFeatX is a tool to help you extract protein features in a fast and efficient way. It contains 32 encodings to help facilitate this process. By extracting these features, you can use them as input for machine learning methods.

TRustDB, a database for Triticum aestivum -Puccinia species protein-protein interactions, provides valuable information about the Puccinia species, which includes various functional protein annotations

We propose deepNEC, a novel end-to-end feature selection and classification model training approach for nitrogen biochemical network-related enzyme prediction.

alfaNET is a database implemented to provide host-pathogen interactome information to aid the development of molecular-based strategies to mitigate bacterial blight impact in Alfalfa.

We present the HuCoPIA database, which contains approximately 100,000 protein-protein interactions between human proteins and three strains (SARS-CoV-2, SARS-CoV and MERS) of betacoronavirus.