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BMC Bioinformatics

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https://www.readbyqxmd.com/read/28327092/metax-a-flexible-and-comprehensive-software-for-processing-metabolomics-data
#1
Bo Wen, Zhanlong Mei, Chunwei Zeng, Siqi Liu
BACKGROUND: Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites. Computational analysis tools that are fully integrated with multiple functions and are easily operated by users who lack extensive knowledge in programing are needed in this research field...
March 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28327091/knn-mdr-a-learning-approach-for-improving-interactions-mapping-performances-in-genome-wide-association-studies
#2
Sinan Abo Alchamlat, Frédéric Farnir
BACKGROUND: Finding epistatic interactions in large association studies like genome-wide association studies (GWAS) with the nowadays-available large volume of genomic data is a challenging and largely unsolved issue. Few previous studies could handle genome-wide data due to the intractable difficulties met in searching a combinatorial explosive search space and statistically evaluating epistatic interactions given a limited number of samples. Our work is a contribution to this field...
March 21, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28320358/preservation-affinity-in-consensus-modules-among-stages-of-hiv-1-progression
#3
Sk Md Mosaddek Hossain, Sumanta Ray, Anirban Mukhopadhyay
BACKGROUND: Analysis of gene expression data provides valuable insights into disease mechanism. Investigating relationship among co-expression modules of different stages is a meaningful tool to understand the way in which a disease progresses. Identifying topological preservation of modular structure also contributes to that understanding. METHODS: HIV-1 disease provides a well-documented progression pattern through three stages of infection: acute, chronic and non-progressor...
March 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28320326/lw-fqzip-2-a-parallelized-reference-based-compression-of-fastq-files
#4
Zhi-An Huang, Zhenkun Wen, Qingjin Deng, Ying Chu, Yiwen Sun, Zexuan Zhu
BACKGROUND: The rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge sequencing data has become a bottleneck of downstream analyses. Data compression is considered as a solution to reduce the dependency on storage. Efficient sequencing data compression methods are highly demanded...
March 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28320324/quickmirseq-a-pipeline-for-quick-and-accurate-quantification-of-both-known-mirnas-and-isomirs-by-jointly-processing-multiple-samples-from-microrna-sequencing
#5
Shanrong Zhao, William Gordon, Sarah Du, Chi Zhang, Wen He, Li Xi, Sachin Mathur, Michael Agostino, Theresa Paradis, David von Schack, Michael Vincent, Baohong Zhang
BACKGROUND: Genome-wide miRNA expression data can be used to study miRNA dysregulation comprehensively. Although many open-source tools for microRNA (miRNA)-seq data analyses are available, challenges remain in accurate miRNA quantification from large-scale miRNA-seq dataset. We implemented a pipeline called QuickMIRSeq for accurate quantification of known miRNAs and miRNA isoforms (isomiRs) from multiple samples simultaneously. RESULTS: QuickMIRSeq considers the unique nature of miRNAs and combines many important features into its implementation...
March 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28320318/encounter-a-parsing-tool-to-uncover-the-mature-n-terminus-of-organelle-targeted-proteins-in-complex-samples
#6
Willy Vincent Bienvenut, Jean-Pierre Scarpelli, Johan Dumestier, Thierry Meinnel, Carmela Giglione
BACKGROUND: Characterization of mature protein N-termini by large scale proteomics is challenging. This is especially true for proteins undergoing cleavage of transit peptides when they are targeted to specific organelles, such as mitochondria or chloroplast. Protein neo-N-termini can be located up to 100-150 amino acids downstream from the initiator methionine and are not easily predictable. Although some bioinformatics tools are available, they usually require extensive manual validation to identify the exact N-terminal position...
March 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28320317/navigo-interactive-tool-for-visualization-and-functional-similarity-and-coherence-analysis-with-gene-ontology
#7
Qing Wei, Ishita K Khan, Ziyun Ding, Satwica Yerneni, Daisuke Kihara
BACKGROUND: The number of genomics and proteomics experiments is growing rapidly, producing an ever-increasing amount of data that are awaiting functional interpretation. A number of function prediction algorithms were developed and improved to enable fast and automatic function annotation. With the well-defined structure and manual curation, Gene Ontology (GO) is the most frequently used vocabulary for representing gene functions. To understand relationship and similarity between GO annotations of genes, it is important to have a convenient pipeline that quantifies and visualizes the GO function analyses in a systematic fashion...
March 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28320310/treetoreads-a-pipeline-for-simulating-raw-reads-from-phylogenies
#8
Emily Jane McTavish, James Pettengill, Steven Davis, Hugh Rand, Errol Strain, Marc Allard, Ruth E Timme
BACKGROUND: Using phylogenomic analysis tools for tracking pathogens has become standard practice in academia, public health agencies, and large industries. Using the same raw read genomic data as input, there are several different approaches being used to infer phylogenetic tree. These include many different SNP pipelines, wgMLST approaches, k-mer algorithms, whole genome alignment and others; each of these has advantages and disadvantages, some have been extensively validated, some are faster, some have higher resolution...
March 20, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28315633/using-simulated-fluorescence-cell-micrographs-for-the-evaluation-of-cell-image-segmentation-algorithms
#9
Veit Wiesmann, Matthias Bergler, Ralf Palmisano, Martin Prinzen, Daniela Franz, Thomas Wittenberg
BACKGROUND: Manual assessment and evaluation of fluorescent micrograph cell experiments is time-consuming and tedious. Automated segmentation pipelines can ensure efficient and reproducible evaluation and analysis with constant high quality for all images of an experiment. Such cell segmentation approaches are usually validated and rated in comparison to manually annotated micrographs. Nevertheless, manual annotations are prone to errors and display inter- and intra-observer variability which influence the validation results of automated cell segmentation pipelines...
March 18, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28302053/a-fast-and-efficient-python-library-for-interfacing-with-the-biological-magnetic-resonance-data-bank
#10
Andrey Smelter, Morgan Astra, Hunter N B Moseley
BACKGROUND: The Biological Magnetic Resonance Data Bank (BMRB) is a public repository of Nuclear Magnetic Resonance (NMR) spectroscopic data of biological macromolecules. It is an important resource for many researchers using NMR to study structural, biophysical, and biochemical properties of biological macromolecules. It is primarily maintained and accessed in a flat file ASCII format known as NMR-STAR. While the format is human readable, the size of most BMRB entries makes computer readability and explicit representation a practical requirement for almost any rigorous systematic analysis...
March 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28302069/bioinformatics-identification-of-new-targets-for-improving-low-temperature-stress-tolerance-in-spring-and-winter-wheat
#11
Alain B Tchagang, François Fauteux, Dan Tulpan, Youlian Pan
BACKGROUND: Phenotypic studies in Triticeae have shown that low temperature-induced protective mechanisms are developmentally regulated and involve dynamic acclimation processes. Understanding these mechanisms is important for breeding cold-resistant wheat cultivars. In this study, we combined three computational techniques for the analysis of gene expression data from spring and winter wheat cultivars subjected to low temperature treatments. Our main objective was to construct a comprehensive network of cold response transcriptional events in wheat, and to identify novel cold tolerance candidate genes in wheat...
March 16, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28302061/subgroup-detection-in-genotype-data-using-invariant-coordinate-selection
#12
Daniel Fischer, Mervi Honkatukia, Maria Tuiskula-Haavisto, Klaus Nordhausen, David Cavero, Rudolf Preisinger, Johanna Vilkki
BACKGROUND: The current gold standard in dimension reduction methods for high-throughput genotype data is the Principle Component Analysis (PCA). The presence of PCA is so dominant, that other methods usually cannot be found in the analyst's toolbox and hence are only rarely applied. RESULTS: We present a modern dimension reduction method called 'Invariant Coordinate Selection' (ICS) and its application to high-throughput genotype data. The more commonly known Independent Component Analysis (ICA) is in this framework just a special case of ICS...
March 16, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28302051/microclass-an-r-package-for-16s-taxonomy-classification
#13
Kristian Hovde Liland, Hilde Vinje, Lars Snipen
BACKGROUND: Taxonomic classification based on the 16S rRNA gene sequence is important for the profiling of microbial communities. In addition to giving the best possible accuracy, it is also important to quantify uncertainties in the classifications. RESULTS: We present an R package with tools for making such classifications, where the heavy computations are implemented in C++ but operated through the standard R interface. The user may train classifiers based on specialized data sets, but we also supply a ready-to-use function trained on a comprehensive training data set designed specifically for this purpose...
March 16, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28298180/bacterial-protein-meta-interactomes-predict-cross-species-interactions-and-protein-function
#14
J Harry Caufield, Christopher Wimble, Semarjit Shary, Stefan Wuchty, Peter Uetz
BACKGROUND: Protein-protein interactions (PPIs) can offer compelling evidence for protein function, especially when viewed in the context of proteome-wide interactomes. Bacteria have been popular subjects of interactome studies: more than six different bacterial species have been the subjects of comprehensive interactome studies while several more have had substantial segments of their proteomes screened for interactions. The protein interactomes of several bacterial species have been completed, including several from prominent human pathogens...
March 16, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28292266/microrna-categorization-using-sequence-motifs-and-k-mers
#15
Malik Yousef, Waleed Khalifa, İlhan Erkin Acar, Jens Allmer
BACKGROUND: Post-transcriptional gene dysregulation can be a hallmark of diseases like cancer and microRNAs (miRNAs) play a key role in the modulation of translation efficiency. Known pre-miRNAs are listed in miRBase, and they have been discovered in a variety of organisms ranging from viruses and microbes to eukaryotic organisms. The computational detection of pre-miRNAs is of great interest, and such approaches usually employ machine learning to discriminate between miRNAs and other sequences...
March 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28292263/cure-smote-algorithm-and-hybrid-algorithm-for-feature-selection-and-parameter-optimization-based-on-random-forests
#16
Li Ma, Suohai Fan
BACKGROUND: The random forests algorithm is a type of classifier with prominent universality, a wide application range, and robustness for avoiding overfitting. But there are still some drawbacks to random forests. Therefore, to improve the performance of random forests, this paper seeks to improve imbalanced data processing, feature selection and parameter optimization. RESULTS: We propose the CURE-SMOTE algorithm for the imbalanced data classification problem...
March 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28292256/a-novel-measure-and-significance-testing-in-data-analysis-of-cell-image-segmentation
#17
Jin Chu Wu, Michael Halter, Raghu N Kacker, John T Elliott, Anne L Plant
BACKGROUND: Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based cell assays in cytometry. Many measures and methods have been proposed and implemented to evaluate segmentation methods. However, computing the standard errors (SE) of the measures and their correlation coefficient is not described, and thus the statistical significance of performance differences between CIS algorithms cannot be assessed...
March 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28288556/guide-picker-is-a-comprehensive-design-tool-for-visualizing-and-selecting-guides-for-crispr-experiments
#18
Soren H Hough, Kris Kancleris, Leigh Brody, Neil Humphryes-Kirilov, Joseph Wolanski, Keith Dunaway, Ayokunmi Ajetunmobi, Victor Dillard
BACKGROUND: Guide Picker ( https://www.deskgen.com/guide-picker/ ) serves as a meta tool for designing CRISPR experiments by presenting ten different guide RNA scoring functions in one simple graphical interface. It allows investigators to simultaneously visualize and sort through every guide targeting the protein-coding regions of any mouse or human gene. RESULTS: Utilizing a multidimensional graphical display featuring two plots and four axes, Guide Picker can analyze all guides while filtering based on four different criteria at a time...
March 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28284194/clonocalc-and-clonoplot-immune-repertoire-analysis-from-raw-files-to-publication-figures-with-graphical-user-interface
#19
Anke Fähnrich, Moritz Krebbel, Normann Decker, Martin Leucker, Felix D Lange, Kathrin Kalies, Steffen Möller
BACKGROUND: Next generation sequencing (NGS) technologies enable studies and analyses of the diversity of both T and B cell receptors (TCR and BCR) in human and animal systems to elucidate immune functions in health and disease. Over the last few years, several algorithms and tools have been developed to support respective analyses of raw sequencing data of the immune repertoire. These tools focus on distinct aspects of the data processing and require a strong bioinformatics background...
March 11, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28284192/most-most-similar-ligand-based-approach-to-target-prediction
#20
Tao Huang, Hong Mi, Cheng-Yuan Lin, Ling Zhao, Linda L D Zhong, Feng-Bin Liu, Ge Zhang, Ai-Ping Lu, Zhao-Xiang Bian
BACKGROUND: Many computational approaches have been used for target prediction, including machine learning, reverse docking, bioactivity spectra analysis, and chemical similarity searching. Recent studies have suggested that chemical similarity searching may be driven by the most-similar ligand. However, the extent of bioactivity of most-similar ligands has been oversimplified or even neglected in these studies, and this has impaired the prediction power. RESULTS: Here we propose the MOst-Similar ligand-based Target inference approach, namely MOST, which uses fingerprint similarity and explicit bioactivity of the most-similar ligands to predict targets of the query compound...
March 11, 2017: BMC Bioinformatics
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