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Fast And Space-Efficient Location Of Heavy Or Dense Segments In Run-Length Encoded Sequences, Ronald I. Greenberg Jan 2018

Fast And Space-Efficient Location Of Heavy Or Dense Segments In Run-Length Encoded Sequences, Ronald I. Greenberg

Ronald Greenberg

This paper considers several variations of an optimization problem with potential applications in such areas as biomolecular sequence analysis and image processing. Given a sequence of items, each with a weight and a length, the goal is to find a subsequence of consecutive items of optimal value, where value is either total weight or total weight divided by total length. There may also be a specified lower and/or upper bound on the acceptable length of subsequences. This paper shows that all the variations of the problem are solvable in linear time and space even with non-uniform item lengths and divisible …


A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti Oct 2017

A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti

Konstantin Läufer

As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 …


A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer Oct 2017

A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer

Konstantin Läufer

RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …


A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti Sep 2017

A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti

Catherine Putonti

As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 …


A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer Sep 2017

A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer

Catherine Putonti

RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …


A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti Jan 2017

A Polyglot Approach To Bioinformatics Data Integration: A Phylogenetic Analysis Of Hiv-1, Steven Reisman, Thomas Hatzopoulous, Konstantin Läufer, George K. Thiruvathukal, Catherine Putonti

George K. Thiruvathukal

As sequencing technologies continue to drop in price and increase in throughput, new challenges emerge for the management and accessibility of genomic sequence data. We have developed a pipeline for facilitating the storage, retrieval, and subsequent analysis of molecular data, integrating both sequence and metadata. Taking a polyglot approach involving multiple languages, libraries, and persistence mechanisms, sequence data can be aggregated from publicly available and local repositories. Data are exposed in the form of a RESTful web service, formatted for easy querying, and retrieved for downstream analyses. As a proof of concept, we have developed a resource for annotated HIV-1 …


Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani Dec 2016

Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani

Jeffrey S. Morris

The advent of high-throughput multi-platform genomics technologies providing whole-genome molecular summaries of biological samples has revolutionalized biomedical research. These technologies yield highly structured big data, whose analysis poses significant quantitative challenges. The field of Bioinformatics has emerged to deal with these challenges, and is comprised of many quantitative and biological scientists working together to eectively process these data and extract the treasure trove of information they contain. Statisticians, with their deep understanding of variability and uncertainty quantification, play a key role in these efforts. In this article, we attempt to summarize some of the key contributions of statisticians to bioinformatics, …


Deciphering The Associations Between Gene Expression And Copy Number Alteration Using A Sparse Double Laplacian Shrinkage Approach, Shuangge Ma Dec 2014

Deciphering The Associations Between Gene Expression And Copy Number Alteration Using A Sparse Double Laplacian Shrinkage Approach, Shuangge Ma

Shuangge Ma

Both gene expression levels (GEs) and copy number alterations (CNAs) have important implications in the development of complex diseases. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The expression of a gene can be regulated by multiple CNAs, and one CNA can regulate the expression of multiple genes. In addition, multiple GEs (CNAs) can be correlated with each other. The existing methods for associating GEs with CNAs have limitations in deciphering the complex data structures. In this study, we develop a sparse double Laplacian shrinkage approach. It jointly models the effects of …


A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma Dec 2014

A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma

Shuangge Ma

In genetic and genomic studies, gene-environment (G*E) interactions have important implications. Some of the existing G$\times$E interaction methods are limited by analyzing a small number of G factors at a time, by assuming linear effects of E factors, by assuming no data contamination, and by adopting ineffective selection techniques. In this study, we propose a new approach for identifying important G*E interactions. It jointly models the effects of all E and G factors and their interactions. A partially linear varying coefficient model (PLVCM) is adopted to accommodate possible nonlinear effects of E factors. A rank-based loss function is used to …


A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer Jul 2013

A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer

George K. Thiruvathukal

RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …


Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder Sep 2008

Word Sense Disambiguation In Biomedical Ontologies With Term Co-Occurrence Analysis And Document Clustering, Bill Andreopoulos, Dimitra Alexopoulou, Michael Schroeder

William B. Andreopoulos

With more and more genomes being sequenced, a lot of effort is devoted to their annotation with terms from controlled vocabularies such as the GeneOntology. Manual annotation based on relevant literature is tedious, but automation of this process is difficult. One particularly challenging problem is word sense disambiguation. Terms such as |development| can refer to developmental biology or to the more general sense. Here, we present two approaches to address this problem by using term co-occurrences and document clustering. To evaluate our method we defined a corpus of 331 documents on development and developmental biology. Term co-occurrence analysis achieves an …


Finding Molecular Complexes Through Multiple Layer Clustering Of Protein Interaction Networks, Bill Andreopoulos, Aijun An, Xiangji Huang, Xiaogang Wang Dec 2006

Finding Molecular Complexes Through Multiple Layer Clustering Of Protein Interaction Networks, Bill Andreopoulos, Aijun An, Xiangji Huang, Xiaogang Wang

William B. Andreopoulos

Clustering protein-protein interaction networks (PINs) helps to identify complexes that guide the cell machinery. Clustering algorithms often create a flat clustering, without considering the layered structure of PINs. We propose the MULIC clustering algorithm that produces layered clusters. We applied MULIC to five PINs. Clusters correlate with known MIPS protein complexes. For example, a cluster of 79 proteins overlaps with a known complex of 88 proteins. Proteins in top cluster layers tend to be more representative of complexes than proteins in bottom layers. Lab work on finding unknown complexes or determining drug effects can be guided by top layer proteins.


Bi-Level Clustering Of Mixed Categorical And Numerical Biomedical Data, Bill Andreopoulos, Aijun An, Xiaogang Wang Jun 2006

Bi-Level Clustering Of Mixed Categorical And Numerical Biomedical Data, Bill Andreopoulos, Aijun An, Xiaogang Wang

William B. Andreopoulos

Biomedical data sets often have mixed categorical and numerical types, where the former represent semantic information on the objects and the latter represent experimental results. We present the BILCOM algorithm for |Bi-Level Clustering of Mixed categorical and numerical data types|. BILCOM performs a pseudo-Bayesian process, where the prior is categorical clustering. BILCOM partitions biomedical data sets of mixed types, such as hepatitis, thyroid disease and yeast gene expression data with Gene Ontology annotations, more accurately than if using one type alone.