Physical Sciences and Mathematics Commons^™

The Maximum Clique Problem: Algorithms, Applications, And Implementations, John David Eblen

Doctoral Dissertations

Computationally hard problems are routinely encountered during the course of solving practical problems. This is commonly dealt with by settling for less than optimal solutions, through the use of heuristics or approximation algorithms. This dissertation examines the alternate possibility of solving such problems exactly, through a detailed study of one particular problem, the maximum clique problem. It discusses algorithms, implementations, and the application of maximum clique results to real-world problems. First, the theoretical roots of the algorithmic method employed are discussed. Then a practical approach is described, which separates out important algorithmic decisions so that the algorithm can be easily …

A Dynamic Energy-Aware Model For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

High Performance Computing (HPC) resources are housed in large datacenters, which consume huge amounts of energy and are quickly demanding attention from businesses as they result in high operating costs. On the other hand HPC environments have been very useful to researchers in many emerging areas in life sciences such as Bioinformatics and Medical Informatics. In this paper, we provide a dynamic model for energy aware scheduling (EAS) in a HPC environment; we use a widely used bioinformatics tool named BLAT (BLAST-like alignment tool) running in a HPC environment as our case study. Our proposed EAS model incorporates 2-Phases: an …

The Gel Documentation System: A Cornerstone To The Implementation Of The Introduction To Biotechnology And Introduction To Bioinformatics Cross-Disciplinary Course Series, Marcy Kelly, Gregory Lampard, Constance Knapp

Cornerstone 3 Reports : Interdisciplinary Informatics

No abstract provided.

Algorithms In Comparative Genomics, Satish Chikkagoudar

Dissertations

The field of comparative genomics is abundant with problems of interest to computer scientists. In this thesis, the author presents solutions to three contemporary problems: obtaining better alignments for phylogeny reconstruction, identifying related RNA sequences in genomes, and ranking Single Nucleotide Polymorphisms (SNPs) in genome-wide association studies (GWAS).

Sequence alignment is a basic and widely used task in bioinformatics. Its applications include identifying protein structure, RNAs and transcription factor binding sites in genomes, and phylogeny reconstruction. Phylogenetic descriptions depend not only on the employed reconstruction technique, but also on the underlying sequence alignment. The author has studied and established a …

Biomedical Relationship Extraction From Literature Based On Bio-Semantic Token Subsequences, Ying Xie, Jayasimha R. Katukuri, Vijay V. Raghavan

Faculty and Research Publications

Relationship Extraction (RE) from biomedical literature is an important and challenging problem in both text mining and bioinformatics. Although various approaches have been proposed to extract protein?protein interaction types, their accuracy rates leave a large room for further exploring. In this paper, two supervised learning algorithms based on newly defined "bio-semantic token subsequence" are proposed for multi-class biomedical relationship classification. The first approach calculates a "bio-semantic token subsequence kernel", whereas the second one explicitly extracts weighted features from bio-semantic token subsequences. The two proposed approaches outperform several alternatives reported in literature on multi-class protein?protein interaction classification.