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Full-Text Articles in Life Sciences
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 …
Error Correction In Next Generation Dna Sequencing Data, Michael Z. Molnar
Error Correction In Next Generation Dna Sequencing Data, Michael Z. Molnar
Electronic Thesis and Dissertation Repository
Motivation: High throughput Next Generation Sequencing (NGS) technologies can sequence the genome of a species quickly and cheaply. Errors that are introduced by NGS technologies limit the full potential of the applications that rely on their data. Current techniques used to correct these errors are not sufficient, and a more efficient and accurate program is needed to correct errors.
Results: We have designed and implemented RACER (Rapid Accurate Correction of Errors in Reads), an error correction program that targets the Illumina genome sequencer, which is currently the dominant NGS technology. RACER combines advanced data structures with an intricate analysis of …