Browsing College of Engineering (MU) by Thesis Advisor "Joshi, Trupti"
Now showing items 1-6 of 6
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Comparative machine learning approach for biomarker identification using multiomics data from patients with endometriosis
(University of Missouri--Columbia, 2019)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide, and causing ... -
Complexity reduction and visualization tool for RDF knowledge network application in precision medicine
(University of Missouri--Columbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Precision medicine is one of the most rapidly emerging areas of research and development, crucial for improving patient care, but there is a lack of ... -
A comprehensive web-based platform for multi-omics data-driven phenotype prediction and marker discovery
(University of Missouri--Columbia, 2023)[EMBARGOED UNTIL 5/1/2024] The G2PDeep-v2 server is a comprehensive web-based platform powered by deep learning, providing phenotype prediction and markers discovery. Despite the availability of similar phenotype prediction ... -
Development of a multi-omics approach to identify highly correlated transcriptomic, proteomic and metabolic signatures in maize B73 and FR697 drought stressed nodal roots
(University of Missouri--Columbia, 2021)Maize is one of the most important crops grown in the continental US and worldwide, and as such, major interest is directed towards understanding the impact of drought conditions on maize growth and development. Nodal ... -
Evolution of soybean knowledge base
(University of Missouri--Columbia, 2015)Soybean Knowledge Base (SoyKB), is a comprehensive web resource for knowledge about soybean genomics and multi-omics data. It is designed to give researchers easier access and better understanding of soybean traits and ... -
Large-scale soybean genome-wide variation workflow and association analysis using deep learning
(University of Missouri--Columbia, 2019)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] With the advances in next-generation sequencing technology and significant reduction in sequencing costs, it is now possible to sequence large collections ...