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BMC Bioinformatics

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https://www.readbyqxmd.com/read/28646877/sbmlmod-a-python-based-web-application-and-web-service-for-efficient-data-integration-and-model-simulation
#1
Sascha Schäuble, Anne-Kristin Stavrum, Mathias Bockwoldt, Pål Puntervoll, Ines Heiland
BACKGROUND: Systems Biology Markup Language (SBML) is the standard model representation and description language in systems biology. Enriching and analysing systems biology models by integrating the multitude of available data, increases the predictive power of these models. This may be a daunting task, which commonly requires bioinformatic competence and scripting. RESULTS: We present SBMLmod, a Python-based web application and service, that automates integration of high throughput data into SBML models...
June 24, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28646874/cmsa-a-heterogeneous-cpu-gpu-computing-system-for-multiple-similar-rna-dna-sequence-alignment
#2
Xi Chen, Chen Wang, Shanjiang Tang, Ce Yu, Quan Zou
BACKGROUND: The multiple sequence alignment (MSA) is a classic and powerful technique for sequence analysis in bioinformatics. With the rapid growth of biological datasets, MSA parallelization becomes necessary to keep its running time in an acceptable level. Although there are a lot of work on MSA problems, their approaches are either insufficient or contain some implicit assumptions that limit the generality of usage. First, the information of users' sequences, including the sizes of datasets and the lengths of sequences, can be of arbitrary values and are generally unknown before submitted, which are unfortunately ignored by previous work...
June 24, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28645323/early-response-index-a-statistic-to-discover-potential-early-stage-disease-biomarkers
#3
Sirajul Salekin, Mehrab Ghanat Bari, Itay Raphael, Thomas G Forsthuber, Jianqiu Michelle Zhang
BACKGROUND: Identifying disease correlated features early before large number of molecules are impacted by disease progression with significant abundance change is very advantageous to biologists for developing early disease diagnosis biomarkers. Disease correlated features have relatively low level of abundance change at early stages. Finding them using existing bioinformatic tools in high throughput data is a challenging task since the technology suffers from limited dynamic range and significant noise...
June 23, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28637426/bioinformatics-indispensable-yet-hidden-in-plain-sight
#4
Andrew Bartlett, Bart Penders, Jamie Lewis
BACKGROUND: Bioinformatics has multitudinous identities, organisational alignments and disciplinary links. This variety allows bioinformaticians and bioinformatic work to contribute to much (if not most) of life science research in profound ways. The multitude of bioinformatic work also translates into a multitude of credit-distribution arrangements, apparently dismissing that work. RESULTS: We report on the epistemic and social arrangements that characterise the relationship between bioinformatics and life science...
June 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28637422/optimal-alpha-reduces-error-rates-in-gene-expression-studies-a-meta-analysis-approach
#5
J F Mudge, C J Martyniuk, J E Houlahan
BACKGROUND: Transcriptomic approaches (microarray and RNA-seq) have been a tremendous advance for molecular science in all disciplines, but they have made interpretation of hypothesis testing more difficult because of the large number of comparisons that are done within an experiment. The result has been a proliferation of techniques aimed at solving the multiple comparisons problem, techniques that have focused primarily on minimizing Type I error with little or no concern about concomitant increases in Type II errors...
June 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28633662/orthored-a-rapid-and-accurate-orthology-prediction-tool-with-low-computational-requirement
#6
Kai Battenberg, Ernest K Lee, Joanna C Chiu, Alison M Berry, Daniel Potter
BACKGROUND: Identifying orthologous genes is an initial step required for phylogenetics, and it is also a common strategy employed in functional genetics to find candidates for functionally equivalent genes across multiple species. At the same time, in silico orthology prediction tools often require large computational resources only available on computing clusters. Here we present OrthoReD, an open-source orthology prediction tool with accuracy comparable to published tools that requires only a desktop computer...
June 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28637421/a-novel-pathway-based-distance-score-enhances-assessment-of-disease-heterogeneity-in-gene-expression
#7
Xiting Yan, Anqi Liang, Jose Gomez, Lauren Cohn, Hongyu Zhao, Geoffrey L Chupp
BACKGROUND: Distance based unsupervised clustering of gene expression data is commonly used to identify heterogeneity in biologic samples. However, high noise levels in gene expression data and relatively high correlation between genes are often encountered, so traditional distances such as Euclidean distance may not be effective at discriminating the biological differences between samples. An alternative method to examine disease phenotypes is to use pre-defined biological pathways. These pathways have been shown to be perturbed in different ways in different subjects who have similar clinical features...
June 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28629355/biologically-constrained-optimization-based-cell-membrane-segmentation-in-c-elegans-embryos
#8
Yusuke Azuma, Shuichi Onami
BACKGROUND: Recent advances in bioimaging and automated analysis methods have enabled the large-scale systematic analysis of cellular dynamics during the embryonic development of Caenorhabditis elegans. Most of these analyses have focused on cell lineage tracing rather than cell shape dynamics. Cell shape analysis requires cell membrane segmentation, which is challenging because of insufficient resolution and image quality. This problem is currently solved by complicated segmentation methods requiring laborious and time consuming parameter adjustments...
June 19, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28629325/quasi-linear-score-for-capturing-heterogeneous-structure-in-biomarkers
#9
Katsuhiro Omae, Osamu Komori, Shinto Eguchi
BACKGROUND: Linear scores are widely used to predict dichotomous outcomes in biomedical studies because of their learnability and understandability. Such approaches, however, cannot be used to elucidate biodiversity when there is heterogeneous structure in target population. RESULTS: Our study was focused on describing intrinsic heterogeneity in predictions. Because heterogeneity can be captured by a clustering method, integrating different information from different clusters should yield better predictions...
June 19, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28629316/a-multiplex-primer-design-algorithm-for-target-amplification-of-continuous-genomic-regions
#10
Ahmet Rasit Ozturk, Tolga Can
BACKGROUND: Targeted Next Generation Sequencing (NGS) assays are cost-efficient and reliable alternatives to Sanger sequencing. For sequencing of very large set of genes, the target enrichment approach is suitable. However, for smaller genomic regions, the target amplification method is more efficient than both the target enrichment method and Sanger sequencing. The major difficulty of the target amplification method is the preparation of amplicons, regarding required time, equipment, and labor...
June 19, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28623901/biomarker-correlation-network-in-colorectal-carcinoma-by-tumor-anatomic-location
#11
Reiko Nishihara, Kimberly Glass, Kosuke Mima, Tsuyoshi Hamada, Jonathan A Nowak, Zhi Rong Qian, Peter Kraft, Edward L Giovannucci, Charles S Fuchs, Andrew T Chan, John Quackenbush, Shuji Ogino, Jukka-Pekka Onnela
BACKGROUND: Colorectal carcinoma evolves through a multitude of molecular events including somatic mutations, epigenetic alterations, and aberrant protein expression, influenced by host immune reactions. One way to interrogate the complex carcinogenic process and interactions between aberrant events is to model a biomarker correlation network. Such a network analysis integrates multidimensional tumor biomarker data to identify key molecular events and pathways that are central to an underlying biological process...
June 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28623888/ub-isap-a-streamlined-unix-pipeline-for-mining-unique-viral-vector-integration-sites-from-next-generation-sequencing-data
#12
Atul Kamboj, Claus V Hallwirth, Ian E Alexander, Geoffrey B McCowage, Belinda Kramer
BACKGROUND: The analysis of viral vector genomic integration sites is an important component in assessing the safety and efficiency of patient treatment using gene therapy. Alongside this clinical application, integration site identification is a key step in the genetic mapping of viral elements in mutagenesis screens that aim to elucidate gene function. RESULTS: We have developed a UNIX-based vector integration site analysis pipeline (Ub-ISAP) that utilises a UNIX-based workflow for automated integration site identification and annotation of both single and paired-end sequencing reads...
June 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28623886/epsilon-cp-using-deep-learning-to-combine-information-from-multiple-sources-for-protein-contact-prediction
#13
Kolja Stahl, Michael Schneider, Oliver Brock
BACKGROUND: Accurately predicted contacts allow to compute the 3D structure of a protein. Since the solution space of native residue-residue contact pairs is very large, it is necessary to leverage information to identify relevant regions of the solution space, i.e. correct contacts. Every additional source of information can contribute to narrowing down candidate regions. Therefore, recent methods combined evolutionary and sequence-based information as well as evolutionary and physicochemical information...
June 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28615003/3d-deep-convolutional-neural-networks-for-amino-acid-environment-similarity-analysis
#14
Wen Torng, Russ B Altman
BACKGROUND: Central to protein biology is the understanding of how structural elements give rise to observed function. The surfeit of protein structural data enables development of computational methods to systematically derive rules governing structural-functional relationships. However, performance of these methods depends critically on the choice of protein structural representation. Most current methods rely on features that are manually selected based on knowledge about protein structures...
June 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28610557/integration-of-quantitated-expression-estimates-from-polya-selected-and-rrna-depleted-rna-seq-libraries
#15
Stephen J Bush, Mary E B McCulloch, Kim M Summers, David A Hume, Emily L Clark
BACKGROUND: The availability of fast alignment-free algorithms has greatly reduced the computational burden of RNA-seq processing, especially for relatively poorly assembled genomes. Using these approaches, previous RNA-seq datasets could potentially be processed and integrated with newly sequenced libraries. Confounding factors in such integration include sequencing depth and methods of RNA extraction and selection. Different selection methods (typically, either polyA-selection or rRNA-depletion) omit different RNAs, resulting in different fractions of the transcriptome being sequenced...
June 13, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28606086/analysis-and-prediction-of-single-stranded-and-double-stranded-dna-binding-proteins-based-on-protein-sequences
#16
Wei Wang, Lin Sun, Shiguang Zhang, Hongjun Zhang, Jinling Shi, Tianhe Xu, Keliang Li
BACKGROUND: DNA-binding proteins perform important functions in a great number of biological activities. DNA-binding proteins can interact with ssDNA (single-stranded DNA) or dsDNA (double-stranded DNA), and DNA-binding proteins can be categorized as single-stranded DNA-binding proteins (SSBs) and double-stranded DNA-binding proteins (DSBs). The identification of DNA-binding proteins from amino acid sequences can help to annotate protein functions and understand the binding specificity...
June 12, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28606054/variable-order-sequence-modeling-improves-bacterial-strain-discrimination-for-ion-torrent-dna-reads
#17
Thomas M Poulsen, Martin Frith
BACKGROUND: Genome sequencing provides a powerful tool for pathogen detection and can help resolve outbreaks that pose public safety and health risks. Mapping of DNA reads to genomes plays a fundamental role in this approach, where accurate alignment and classification of sequencing data is crucial. Standard mapping methods crudely treat bases as independent from their neighbors. Accuracy might be improved by using higher order paired hidden Markov models (HMMs), which model neighbor effects, but introduce design and implementation issues that have typically made them impractical for read mapping applications...
June 12, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28617231/atria-a-novel-centrality-algorithm-applied-to-biological-networks
#18
Trevor Cickovski, Eli Peake, Vanessa Aguiar-Pulido, Giri Narasimhan
BACKGROUND: The notion of centrality is used to identify "important" nodes in social networks. Importance of nodes is not well-defined, and many different notions exist in the literature. The challenge of defining centrality in meaningful ways when network edges can be positively or negatively weighted has not been adequately addressed in the literature. Existing centrality algorithms also have a second shortcoming, i.e., the list of the most central nodes are often clustered in a specific region of the network and are not well represented across the network...
June 7, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28617230/predicting-anatomic-therapeutic-chemical-classification-codes-using-tiered-learning
#19
Thomas Olson, Rahul Singh
BACKGROUND: The low success rate and high cost of drug discovery requires the development of new paradigms to identify molecules of therapeutic value. The Anatomical Therapeutic Chemical (ATC) Code System is a World Health Organization (WHO) proposed classification that assigns multi-level codes to compounds based on their therapeutic, pharmacological and chemical characteristics as well as the in-vivo sites(s) of activity. The ability to predict ATC codes of compounds can assist in creation of high-quality chemical libraries for drug screening and in applications such as drug repositioning...
June 7, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28617225/a-greedy-alignment-free-distance-estimator-for-phylogenetic-inference
#20
Sharma V Thankachan, Sriram P Chockalingam, Yongchao Liu, Ambujam Krishnan, Srinivas Aluru
BACKGROUND: Alignment-free sequence comparison approaches have been garnering increasing interest in various data- and compute-intensive applications such as phylogenetic inference for large-scale sequences. While k-mer based methods are predominantly used in real applications, the average common substring (ACS) approach is emerging as one of the prominent alignment-free approaches. This ACS approach has been further generalized by some recent work, either greedily or exactly, by allowing a bounded number of mismatches in the common substrings...
June 7, 2017: BMC Bioinformatics
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