Open Access. Powered by Scholars. Published by Universities.®
Artificial Intelligence and Robotics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Artificial Intelligence and Robotics
Machine Learning With Digital Signal Processing For Rapid And Accurate Alignment-Free Genome Analysis: From Methodological Design To A Covid-19 Case Study, Gurjit Singh Randhawa
Machine Learning With Digital Signal Processing For Rapid And Accurate Alignment-Free Genome Analysis: From Methodological Design To A Covid-19 Case Study, Gurjit Singh Randhawa
Electronic Thesis and Dissertation Repository
In the field of bioinformatics, taxonomic classification is the scientific practice of identifying, naming, and grouping of organisms based on their similarities and differences. The problem of taxonomic classification is of immense importance considering that nearly 86% of existing species on Earth and 91% of marine species remain unclassified. Due to the magnitude of the datasets, the need exists for an approach and software tool that is scalable enough to handle large datasets and can be used for rapid sequence comparison and analysis. We propose ML-DSP, a stand-alone alignment-free software tool that uses Machine Learning and Digital Signal Processing to …
Nbpmf: Novel Network-Based Inference Methods For Peptide Mass Fingerprinting, Zhewei Liang
Nbpmf: Novel Network-Based Inference Methods For Peptide Mass Fingerprinting, Zhewei Liang
Electronic Thesis and Dissertation Repository
Proteins are large, complex molecules that perform a vast array of functions in every living cell. A proteome is a set of proteins produced in an organism, and proteomics is the large-scale study of proteomes. Several high-throughput technologies have been developed in proteomics, where the most commonly applied are mass spectrometry (MS) based approaches. MS is an analytical technique for determining the composition of a sample. Recently it has become a primary tool for protein identification, quantification, and post translational modification (PTM) characterization in proteomics research. There are usually two different ways to identify proteins: top-down and bottom-up. Top-down approaches …
Signet: A Neural Network Architecture For Predicting Protein-Protein Interactions, Muhammad S. Ahmed
Signet: A Neural Network Architecture For Predicting Protein-Protein Interactions, Muhammad S. Ahmed
Electronic Thesis and Dissertation Repository
The study of protein-protein interactions (PPI) is critically important within the field of Molecular Biology, as proteins facilitate key organismal functions including the maintenance of both cellular structure and function. Current experimental methods for elucidating PPIs are greatly hindered by large operating costs, lengthy wait times, as well as low accuracy. The recent development of computational PPI predicting techniques has worked to address many of these issues. Despite this, many of these methods utilize over-engineered features and naive learning algorithms. With the recent advances in Machine Learning and Artificial Intelligence, we attempt to view this problem through a novel, deep …