Although we have made progress in reducing mortality and morbidity rates in a number of human diseases through early detection and adjuvant therapy, the interventions inferred from conventional disease management and ...
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Although we have made progress in reducing mortality and morbidity rates in a number of human diseases through early detection and adjuvant therapy, the interventions inferred from conventional disease management and clinical care systems, such as those in cancers and neurological diseases, still lack discrimination and come at considerable emotional, physical, and financial cost. Complex diseases exhibit complex phenotypes, and proper diagnosis at the point-of-care requires that the analysis take into account the patient's history and exposure to environmental factors, as well as genotype and phenotype information.
This project represents an interdisciplinary approach to integrating computational methods into the knowledge-discovery process associated with understanding biological systems impacted by the loss or destruction of s...
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This project represents an interdisciplinary approach to integrating computational methods into the knowledge-discovery process associated with understanding biological systems impacted by the loss or destruction of sensitive habitats. We specifically developed bioinformatics tools for the study of (1) beach mouse communities and (2) marginal fish habitats. Data mining was used in these projects to intelligently query databases and to elucidate broad patterns that facilitate overall data interpretation. Visualization techniques that were developed present mined data in ways where context, perceptual cues, and spatial reasoning skills can be applied to uncover significant trends in behavioral patterns, habitat use, species diversity, and community composition.
bioinformatics software often integrates multiple off-the-shelf programs into a single compute pipeline. Each standalone program generates output, that is frequently saved into a plain-text file, which is then process...
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ISBN:
(纸本)9781728173030
bioinformatics software often integrates multiple off-the-shelf programs into a single compute pipeline. Each standalone program generates output, that is frequently saved into a plain-text file, which is then processed as input by the program that is responsible for the next stage of the computation. Modern advances in genome sequencing and protein structure resolution methods have yielded large amounts of data, that when processed by bioinformatics compute pipelines, results in vast numbers of file reads and writes. Since computation capabilities of large-scale distributed systems grow much faster than their I/O bandwidth, processing such big data using these compute pipelines will not scale as the amount of data grows. For this work, we motivate and demonstrate a dynamic interception-based I/O analysis tool to assess the file read and write characteristics of a protein mutation generation pipeline. We discuss how our analysis tool can be further extended to apply compression and in-site analysis and has the potential to scale UO-intensive bioinformatics applications on high performance computing (HPC) systems.
Biological knowledge discovery is a tedious task which relies on computationally intensive analyses to process huge volumes of data and metadata. This task can be facilitated by a well-designed workflow management sys...
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The proceedings contain 38 papers. The topics discussed include: a multiobjective evolutionary algorithm for colon cancer biomarkers identification on gene expression data;machine learning identifies novel microRNA bi...
ISBN:
(纸本)9798350356632
The proceedings contain 38 papers. The topics discussed include: a multiobjective evolutionary algorithm for colon cancer biomarkers identification on gene expression data;machine learning identifies novel microRNA biomarkers predictive for gastric cancer;methods for analyzing swallowing sound in dysphagia care: a telemedicine approach;a fast feature selection for interpretable modeling based on fuzzy inference systems;improving machine learning based sepsis diagnosis using heart rate variability;machine learning and gut microbiome for breast cancer screening;comprehensive modeling and question answering of cancer clinical practice guidelines using LLMs;and predicting metabolic reactions with a molecular transformer for drug design optimization.
The proceedings contain 40 papers. The topics discussed include: an effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy;control strategies for intelli...
ISBN:
(纸本)9781467394727
The proceedings contain 40 papers. The topics discussed include: an effective approach to identify gene-gene interactions for complex quantitative traits using generalized fuzzy accuracy;control strategies for intelligent adjustment of pressure in intermittent pneumatic compression systems;protein fold identification using machine learning methods on contact maps;compressed sensing denoising for segmentation of localization microscopy data;computational prediction of bacterial type iv-b effectors using c-terminal signals and machine learning algorithms;a cross-entropy method for change-point detection in four-letter DNA sequences;gene selection using interaction information for microarray-based cancer classification;and computational intelligence for metabolic pathway design: application to the pentose phosphate pathway.
The proceedings contains 73 papers from the conference on Fourth ieee Symposium on bioinformatics and Bioengineering, BIBE 2004. The topics discussed include: techniques for enhancing computation of DNA curvature mole...
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ISBN:
(纸本)0769521738
The proceedings contains 73 papers from the conference on Fourth ieee Symposium on bioinformatics and Bioengineering, BIBE 2004. The topics discussed include: techniques for enhancing computation of DNA curvature molecules;towards automating an interventional radiological procedure;reducing the computational load of energy evaluations for protein folding;segmentation of the sylvian fissure in brain MR images;biomedical ontologies in post-genomic information systems;identifying significant genes from microarray data;good spaced seeds for homology search;and estimating seed sensitivity on homogeneous alignments.
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