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Full-Text Articles in Physical Sciences and Mathematics

Venn, A Tool For Titrating Sequence Conservation Onto Protein Structures, Jay Vyas, Michael R. Gryk, Martin R. Schiller Oct 2009

Venn, A Tool For Titrating Sequence Conservation Onto Protein Structures, Jay Vyas, Michael R. Gryk, Martin R. Schiller

Life Sciences Faculty Research

Residue conservation is an important, established method for inferring protein function, modularity and specificity. It is important to recognize that it is the 3D spatial orientation of residues that drives sequence conservation. Considering this, we have built a new computational tool, VENN that allows researchers to interactively and graphically titrate sequence homology onto surface representations of protein structures. Our proposed titration strategies reveal critical details that are not readily identified using other existing tools. Analyses of a bZIP transcription factor and receptor recognition of Fibroblast Growth Factor using VENN revealed key specificity determinants. Weblink: http://sbtools.uchc.edu/venn/.


A Proposed Syntax For Minimotif Semantics, Version 1., Jay Vyas, Ronald J. Nowling, Mark W. Maciejewski, Sanguthevar Rajasekaran, Michael R. Gryk, Martin R. Schiller Aug 2009

A Proposed Syntax For Minimotif Semantics, Version 1., Jay Vyas, Ronald J. Nowling, Mark W. Maciejewski, Sanguthevar Rajasekaran, Michael R. Gryk, Martin R. Schiller

Life Sciences Faculty Research

BACKGROUND:

One of the most important developments in bioinformatics over the past few decades has been the observation that short linear peptide sequences (minimotifs) mediate many classes of cellular functions such as protein-protein interactions, molecular trafficking and post-translational modifications. As both the creators and curators of a database which catalogues minimotifs, Minimotif Miner, the authors have a unique perspective on the commonalities of the many functional roles of minimotifs. There is an obvious usefulness in standardizing functional annotations both in allowing for the facile exchange of data between various bioinformatics resources, as well as the internal clustering of sets of …


A Study Of Relevance Feedback In Vector Space Model, Deepthi Katta May 2009

A Study Of Relevance Feedback In Vector Space Model, Deepthi Katta

UNLV Theses, Dissertations, Professional Papers, and Capstones

Information Retrieval is the science of searching for information or documents based on information need from a huge set of documents. It has been an active field of research since early 19th century and different models of retrieval came in to existence to cater the information need.

This thesis starts with understanding some of the basic information retrieval models, followed by implementation of one of the most popular statistical retrieval model known as Vector Space Model. This model ranks the documents in the collection based on the similarity measure calculated between the query and the respective document. The user …


A Survey Of Monge Properties, Swetha Sethumadhavan May 2009

A Survey Of Monge Properties, Swetha Sethumadhavan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Monge properties play an important role in theoretical computer science. Many greedy algorithms are based on such properties, as is speedup in dynamic programming. Monge properties are simple monotonicity properties which are observed and used in various settings such as resource optimization, computational geometry, statistical sampling, computational biology and coding.


Turn Constrained Path Planning Problems, Victor M. Roman May 2009

Turn Constrained Path Planning Problems, Victor M. Roman

UNLV Theses, Dissertations, Professional Papers, and Capstones

We consider the problem of constructing multiple disjoint paths connecting a source point s to a target point t in a geometric graph. We require that the paths do not have any sharp turn angles. We present a review of turn constrained path planning algorithms and also algorithms for constructing disjoint paths. We then combine these techniques and present an O(nlogn) time algorithm for constructing a pair of edge disjoint turn constrained paths connecting two nodes in a planar geometric graph. We also consider the development of a turn constrained shortest path map in the presence of …


Minimotif Miner 2nd Release: A Database And Web System For Motif Search, Sanguthevar Rajasekaran, Sudha Balla, Patrick R. Gradie, Michael R. Gryk, Krishna Kadaveru, Vamsi Kundeti, Mark W. Maciejewski, Tian Mi, Nicholas Rubino, Jay Vyas, Martin R. Schiller Jan 2009

Minimotif Miner 2nd Release: A Database And Web System For Motif Search, Sanguthevar Rajasekaran, Sudha Balla, Patrick R. Gradie, Michael R. Gryk, Krishna Kadaveru, Vamsi Kundeti, Mark W. Maciejewski, Tian Mi, Nicholas Rubino, Jay Vyas, Martin R. Schiller

Life Sciences Faculty Research

Minimotif Miner (MnM) consists of a minimotif database and a web-based application that enables prediction of motif-based functions in user-supplied protein queries. We have revised MnM by expanding the database more than 10-fold to approximately 5000 motifs and standardized the motif function definitions. The web-application user interface has been redeveloped with new features including improved navigation, screencast-driven help, support for alias names and expanded SNP analysis. A sample analysis of prion shows how MnM 2 can be used.


Effects Of Similarity Metrics On Document Clustering, Rushikesh Veni Jan 2009

Effects Of Similarity Metrics On Document Clustering, Rushikesh Veni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Document clustering or unsupervised document classification is an automated process of grouping documents with similar content. A typical technique uses a similarity function to compare documents. In the literature, many similarity functions such as dot product or cosine measures are proposed for the comparison operator.

For the thesis, we evaluate the effects a similarity function may have on clustering. We start by representing a document and a query, both as a vector of high-dimensional space corresponding to the keywords followed by using an appropriate distance measure in k-means to compute similarity between the document vector and the query vector to …


Efficient Clustering Techniques For Managing Large Datasets, Vasanth Nemala Jan 2009

Efficient Clustering Techniques For Managing Large Datasets, Vasanth Nemala

UNLV Theses, Dissertations, Professional Papers, and Capstones

The result set produced by a search engine in response to the user query is very large. It is typically the responsibility of the user to browse the result set to identify relevant documents. Many tools have been developed to assist the user to identify the most relevant documents. One such a tool is clustering technique. In this method, the closely related documents are grouped based on their contents. Hence if a document turns out to be relevant, so are the rest of the documents in the cluster. So it would be easy for a user to sift through the …


Hierarchical Routing In Manets Using Simple Clustering, Adam Carnine Jan 2009

Hierarchical Routing In Manets Using Simple Clustering, Adam Carnine

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents both a review of current MANET routing protocols and a new MANET routing algorithm. The routing protocols reviewed include representative samples from the three primary forms of routing found in MANETS: proactive routing, reactive routing and hybrid routing. Secure algorithms are given special treatment in the review. In addition several protocol enhancements are discussed.

The proposed routing protocol is designed to support networks of a medium size, containing over 200 nodes but less than 3,000 nodes. The design is intentionally simple to allow ease of implementation in comparison with other MANET protocols that provide similar functionality.