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Articles 1 - 14 of 14
Full-Text Articles in Computational Biology
Mirwip: Microrna Target Prediction Based On Microrna-Containing Ribonucleoprotein-Enriched Transcripts, Molly Hammell, Dang Long, Liang Zhang, Andrew Lee, C. Steven Carmack, Min Han, Ye Ding, Victor Ambros
Mirwip: Microrna Target Prediction Based On Microrna-Containing Ribonucleoprotein-Enriched Transcripts, Molly Hammell, Dang Long, Liang Zhang, Andrew Lee, C. Steven Carmack, Min Han, Ye Ding, Victor Ambros
Victor R. Ambros
Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNA-target interactions. Recently, a dataset of 3,404 miRNA-associated mRNA transcripts was identified by immunoprecipitation of the RNA-induced silencing complex components AIN-1 and AIN-2. Our analysis of this AIN-IP dataset revealed enrichment for defining characteristics of functional miRNA-target interactions, including structural accessibility of target sequences, total free energy of miRNA-target hybridization and topology of base-pairing to the 5' seed region of the miRNA. We used these enriched characteristics as the basis for a quantitative miRNA target prediction method, …
Immunopurification Of Ago1 Mirnps Selects For A Distinct Class Of Microrna Targets, Xin Hong, Molly Hammell, Victor Ambros, Stephen Cohen
Immunopurification Of Ago1 Mirnps Selects For A Distinct Class Of Microrna Targets, Xin Hong, Molly Hammell, Victor Ambros, Stephen Cohen
Victor R. Ambros
microRNAs comprise a few percent of animal genes and have been recognized as important regulators of a diverse range of biological processes. Understanding the biological functions of miRNAs requires effective means to identify their targets. Combined efforts from computational prediction, miRNA over-expression or depletion, and biochemical purification have identified thousands of potential miRNA-target pairs in cells and organisms. Complementarity to the miRNA seed sequence appears to be a common principle in target recognition. Other features, including miRNA-target duplex stability, binding site accessibility, and local UTR structure might affect target recognition. Yet computational approaches using such contextual features have yielded largely …
Three-Dimensional Confocal Microscopy Indentation Method For Hydrogel Elasticity Measurement, Donghee Lee, Md Mahmudur Rahman, You Zhou, Sangjin Ryu
Three-Dimensional Confocal Microscopy Indentation Method For Hydrogel Elasticity Measurement, Donghee Lee, Md Mahmudur Rahman, You Zhou, Sangjin Ryu
Md Mahmudur Rahman
No abstract provided.
Proteomic Characterization Of Her-2/Neu-Overexpressing Breast Cancer Cells, Hexin Chen, G. Pimienta, Y. Gu, X. Sun, Jianjun Hu, M.-S. Kim, R. Chaerkady, M. Gucek, R. Cole, S. Sukumar, A. Pandey
Proteomic Characterization Of Her-2/Neu-Overexpressing Breast Cancer Cells, Hexin Chen, G. Pimienta, Y. Gu, X. Sun, Jianjun Hu, M.-S. Kim, R. Chaerkady, M. Gucek, R. Cole, S. Sukumar, A. Pandey
Jianjun Hu
No abstract provided.
Positive Selection Drives Preferred Segment Combinations During Influenza Virus Reassortment, Konstantin Zeldovich, Ping Liu, Nicholas Renzette, Matthieu Foll, Serena Pham, Sergey Venev, Glen Gallagher, Daniel Bolon, Evelyn Kurt-Jones, Jeffrey Jensen, Daniel Caffrey, Celia Schiffer, Timothy Kowalik, Jennifer Wang, Robert Finberg
Positive Selection Drives Preferred Segment Combinations During Influenza Virus Reassortment, Konstantin Zeldovich, Ping Liu, Nicholas Renzette, Matthieu Foll, Serena Pham, Sergey Venev, Glen Gallagher, Daniel Bolon, Evelyn Kurt-Jones, Jeffrey Jensen, Daniel Caffrey, Celia Schiffer, Timothy Kowalik, Jennifer Wang, Robert Finberg
Celia A. Schiffer
Influenza A virus (IAV) has a segmented genome that allows for the exchange of genome segments between different strains. This reassortment accelerates evolution by breaking linkage, helping IAV cross species barriers to potentially create highly virulent strains. Challenges associated with monitoring the process of reassortment in molecular detail have limited our understanding of its evolutionary implications. We applied a novel deep sequencing approach with quantitative analysis to assess the in vitro temporal evolution of genomic reassortment in IAV. The combination of H1N1 and H3N2 strains reproducibly generated a new H1N2 strain with the hemagglutinin and nucleoprotein segments originating from H1N1 …
A Quantitative Rna Code For Mrna Target Selection By The Germline Fate Determinant Gld-1, Jane Wright, Dimos Gaidatzis, Mathias Senften, Brian Farley, Eric Westhof, Sean Ryder, Rafal Ciosk
A Quantitative Rna Code For Mrna Target Selection By The Germline Fate Determinant Gld-1, Jane Wright, Dimos Gaidatzis, Mathias Senften, Brian Farley, Eric Westhof, Sean Ryder, Rafal Ciosk
Sean P. Ryder
RNA-binding proteins (RBPs) are critical regulators of gene expression. To understand and predict the outcome of RBP-mediated regulation a comprehensive analysis of their interaction with RNA is necessary. The signal transduction and activation of RNA (STAR) family of RBPs includes developmental regulators and tumour suppressors such as Caenorhabditis elegans GLD-1, which is a key regulator of germ cell development. To obtain a comprehensive picture of GLD-1 interactions with the transcriptome, we identified GLD-1-associated mRNAs by RNA immunoprecipitation followed by microarray detection. Based on the computational analysis of these mRNAs we generated a predictive model, where GLD-1 association with mRNA is …
Influenza Virus Drug Resistance: A Time-Sampled Population Genetics Perspective, Matthieu Foll, Yu Poh, Nicholas Renzette, Anna Admetlla, Claudia Bank, Hyunjin Shim, Anna Malaspinas, Gregory Ewing, Ping Liu, Daniel Wegmann, Daniel Caffrey, Konstantin Zeldovich, Daniel Bolon, Jennifer Wang, Timothy Kowalik, Celia Schiffer, Robert Finberg, Jeffrey Jensen
Influenza Virus Drug Resistance: A Time-Sampled Population Genetics Perspective, Matthieu Foll, Yu Poh, Nicholas Renzette, Anna Admetlla, Claudia Bank, Hyunjin Shim, Anna Malaspinas, Gregory Ewing, Ping Liu, Daniel Wegmann, Daniel Caffrey, Konstantin Zeldovich, Daniel Bolon, Jennifer Wang, Timothy Kowalik, Celia Schiffer, Robert Finberg, Jeffrey Jensen
Celia A. Schiffer
The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence …
Bloom-Forming Cyanobacteria And Other Phytoplankton In Northern New Jersey Freshwater Bodies, Tin-Chun Chu, Matthew Rienzo
Bloom-Forming Cyanobacteria And Other Phytoplankton In Northern New Jersey Freshwater Bodies, Tin-Chun Chu, Matthew Rienzo
Tin-Chun Chu, Ph.D.
No abstract provided.
Recent Progress In Polymorphism-Based Population Genetic Inference., Jessica Crisci, Yu-Ping Poh, Angela Bean, Alfred Simkin, Jeffrey Jensen
Recent Progress In Polymorphism-Based Population Genetic Inference., Jessica Crisci, Yu-Ping Poh, Angela Bean, Alfred Simkin, Jeffrey Jensen
Jessica L Crisci
The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also …
Exploring The Role Of The Solvent In The Denaturation Of A Protein: A Molecular Dynamics Study Of The Dna Binding Domain Of The 434 Repressor, Celia Schiffer, Volker Dötsch, Kurt Wuthrich, Wilfred Van Gunsteren
Exploring The Role Of The Solvent In The Denaturation Of A Protein: A Molecular Dynamics Study Of The Dna Binding Domain Of The 434 Repressor, Celia Schiffer, Volker Dötsch, Kurt Wuthrich, Wilfred Van Gunsteren
Celia A. Schiffer
Molecular dynamics simulations of the DNA binding domain of 434 repressor are presented which aim at unraveling the role of solvent in protein denaturation. Four altered solvent models, each mimicking various possible aspects of the addition of a denaturant to the aqueous solvent, were used in the simulations to analyze their effects on the stability of the protein. The solvent was altered by selectively changing the Coulombic interaction between water and protein atoms and between different water molecules. The use of a modified solvent model has the advantage of mimicking the presence of denaturant without having denaturant molecules present in …
Clustering With Exclusion Zones: Genomic Applications, Mark Segal, Yuanyuan Xiao, Fred Huffer
Clustering With Exclusion Zones: Genomic Applications, Mark Segal, Yuanyuan Xiao, Fred Huffer
Mark R Segal
Methods for formally evaluating the clustering of events in space or time, notably the scan statistic, have been richly developed and widely applied. In order to utilize the scan statistic and related approaches, it is necessary to know the extent of the spatial or temporal domains wherein the events arise. Implicit in their usage is that these domains have no “holes”—hereafter “exclusion zones”—regions in which events a priori cannot occur. However, in many contexts, this requirement is not met. When the exclusion zones are known, it is straightforward to correct the scan statistic for their occurrence by simply adjusting the …
Identification Of Yeast Transcriptional Regulation Networks Using Multivariate Random Forests, Yuanyuan Xiao, Mark Segal
Identification Of Yeast Transcriptional Regulation Networks Using Multivariate Random Forests, Yuanyuan Xiao, Mark Segal
Mark R Segal
The recent availability of whole-genome scale data sets that investigate complementary and diverse aspects of transcriptional regulation has spawned an increased need for new and effective computational approaches to analyze and integrate these large scale assays. Here, we propose a novel algorithm, based on random forest methodology, to relate gene expression (as derived from expression microarrays) to sequence features residing in gene promoters (as derived from DNA motif data) and transcription factor binding to gene promoters (as derived from tiling microarrays). We extend the random forest approach to model a multivariate response as represented, for example, by time-course gene expression …
Chess, Chance And Conspiracy, Mark Segal
Chess, Chance And Conspiracy, Mark Segal
Mark R Segal
Chess and chance are seemingly strange bedfellows. Luck and/or randomness have no apparent role in move selection when the game is played at the highest levels. However, when competition is at the ultimate level, that of the World Chess Championship (WCC), chess and conspiracy are not strange bedfellows, there being a long and colorful history of accusations levied between participants. One such accusation, frequently repeated, was that all the games in the 1985 WCC (Karpov vs Kasparov) were fixed and prearranged move by move. That this claim was advanced by a former World Champion, Bobby Fischer, argues that it ought …
Bioinformatic Analysis Of The Metal-Binding Protein Families And Heavy Metal Resistance Amongst Cyanobacteria, Tin-Chun Chu, Lee Lee, Shankar Srinivasan
Bioinformatic Analysis Of The Metal-Binding Protein Families And Heavy Metal Resistance Amongst Cyanobacteria, Tin-Chun Chu, Lee Lee, Shankar Srinivasan
Tin-Chun Chu, Ph.D.
No abstract provided.