journal
MENU ▼
Read by QxMD icon Read
search

BMC Bioinformatics

journal
https://www.readbyqxmd.com/read/27809781/pse-hmm-genome-wide-cnv-detection-from-ngs-data-using-an-hmm-with-position-specific-emission-probabilities
#1
Seyed Amir Malekpour, Hamid Pezeshk, Mehdi Sadeghi
BACKGROUND: Copy Number Variation (CNV) is envisaged to be a major source of large structural variations in the human genome. In recent years, many studies apply Next Generation Sequencing (NGS) data for the CNV detection. However, still there is a necessity to invent more accurate computational tools. RESULTS: In this study, mate pair NGS data are used for the CNV detection in a Hidden Markov Model (HMM). The proposed HMM has position specific emission probabilities, i...
November 3, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/27806697/evaluating-tools-for-transcription-factor-binding-site-prediction
#2
Narayan Jayaram, Daniel Usvyat, Andrew C R Martin
BACKGROUND: Binding of transcription factors to transcription factor binding sites (TFBSs) is key to the mediation of transcriptional regulation. Information on experimentally validated functional TFBSs is limited and consequently there is a need for accurate prediction of TFBSs for gene annotation and in applications such as evaluating the effects of single nucleotide variations in causing disease. TFBSs are generally recognized by scanning a position weight matrix (PWM) against DNA using one of a number of available computer programs...
November 2, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/27806691/indel-marker-detection-by-integration-of-multiple-softwares-using-machine-learning-techniques
#3
Jianqiu Yang, Xinyi Shi, Lun Hu, Daipeng Luo, Jing Peng, Shengwu Xiong, Fanjing Kong, Baohui Liu, Xiaohui Yuan
BACKGROUND: In the biological experiments of soybean species, molecular markers are widely used to verify the soybean genome or construct its genetic map. Among a variety of molecular markers, insertions and deletions (InDels) are preferred with the advantages of wide distribution and high density at the whole-genome level. Hence, the problem of detecting InDels based on next-generation sequencing data is of great importance for the design of InDel markers. To tackle it, this paper integrated machine learning techniques with existing software and developed two algorithms for InDel detection, one is the best F-score method (BF-M) and the other is the Support Vector Machine (SVM) method (SVM-M), which is based on the classical SVM model...
November 2, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/28100166/smite-an-r-bioconductor-package-that-identifies-network-modules-by-integrating-genomic-and-epigenomic-information
#4
N Ari Wijetunga, Andrew D Johnston, Ryo Maekawa, Fabien Delahaye, Netha Ulahannan, Kami Kim, John M Greally
BACKGROUND: The molecular assays that test gene expression, transcriptional, and epigenetic regulation are increasingly diverse and numerous. The information generated by each type of assay individually gives an insight into the state of the cells tested. What should be possible is to add the information derived from separate, complementary assays to gain higher-confidence insights into cellular states. At present, the analysis of multi-dimensional, massive genome-wide data requires an initial pruning step to create manageable subsets of observations that are then used for integration, which decreases the sizes of the intersecting data sets and the potential for biological insights...
January 18, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28095799/multidataset-an-r-package-for-encapsulating-multiple-data-sets-with-application-to-omic-data-integration
#5
Carles Hernandez-Ferrer, Carlos Ruiz-Arenas, Alba Beltran-Gomila, Juan R González
BACKGROUND: Reduction in the cost of genomic assays has generated large amounts of biomedical-related data. As a result, current studies perform multiple experiments in the same subjects. While Bioconductor's methods and classes implemented in different packages manage individual experiments, there is not a standard class to properly manage different omic datasets from the same subjects. In addition, most R/Bioconductor packages that have been designed to integrate and visualize biological data often use basic data structures with no clear general methods, such as subsetting or selecting samples...
January 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28095781/link-prediction-in-drug-target-interactions-network-using-similarity-indices
#6
Yiding Lu, Yufan Guo, Anna Korhonen
BACKGROUND: In silico drug-target interaction (DTI) prediction plays an integral role in drug repositioning: the discovery of new uses for existing drugs. One popular method of drug repositioning is network-based DTI prediction, which uses complex network theory to predict DTIs from a drug-target network. Currently, most network-based DTI prediction is based on machine learning - methods such as Restricted Boltzmann Machines (RBM) or Support Vector Machines (SVM). These methods require additional information about the characteristics of drugs, targets and DTIs, such as chemical structure, genome sequence, binding types, causes of interactions, etc...
January 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28095775/ara-peps-a-repository-of-putative-sorf-encoded-peptides-in-arabidopsis-thaliana
#7
Rashmi R Hazarika, Barbara De Coninck, Lidia R Yamamoto, Laura R Martin, Bruno P A Cammue, Vera van Noort
BACKGROUND: Many eukaryotic RNAs have been considered non-coding as they only contain short open reading frames (sORFs). However, there is increasing evidence for the translation of these sORFs into bioactive peptides with potent signaling, antimicrobial, developmental, antioxidant roles etc. Yet only a few peptides encoded by sORFs are annotated in the model organism Arabidopsis thaliana. RESULTS: To aid the functional annotation of these peptides, we have developed ARA-PEPs (available at http://www...
January 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28095772/empirical-assessment-of-analysis-workflows-for-differential-expression-analysis-of-human-samples-using-rna-seq
#8
Claire R Williams, Alyssa Baccarella, Jay Z Parrish, Charles C Kim
BACKGROUND: RNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression modeling, and identification of differentially expressed genes. Although some studies have benchmarked these tools against gold standard gene expression sets, few have evaluated their performance in concert with one another...
January 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28095769/pcm-sabre-a-platform-for-benchmarking-and-comparing-outcome-prediction-methods-in-precision-cancer-medicine
#9
Noah Eyal-Altman, Mark Last, Eitan Rubin
BACKGROUND: Numerous publications attempt to predict cancer survival outcome from gene expression data using machine-learning methods. A direct comparison of these works is challenging for the following reasons: (1) inconsistent measures used to evaluate the performance of different models, and (2) incomplete specification of critical stages in the process of knowledge discovery. There is a need for a platform that would allow researchers to replicate previous works and to test the impact of changes in the knowledge discovery process on the accuracy of the induced models...
January 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28088191/predicting-probable-alzheimer-s-disease-using-linguistic-deficits-and-biomarkers
#10
Sylvester O Orimaye, Jojo S-M Wong, Karen J Golden, Chee P Wong, Ireneous N Soyiri
BACKGROUND: The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population...
January 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28088185/igc-an-integrated-analysis-package-of-gene-expression-and-copy-number-alteration
#11
Yi-Pin Lai, Liang-Bo Wang, Wei-An Wang, Liang-Chuan Lai, Mong-Hsun Tsai, Tzu-Pin Lu, Eric Y Chuang
BACKGROUND: With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual...
January 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28088176/ttca-an-r-package-for-the-identification-of-differentially-expressed-genes-in-time-course-microarray-data
#12
Marco Albrecht, Damian Stichel, Benedikt Müller, Ruth Merkle, Carsten Sticht, Norbert Gretz, Ursula Klingmüller, Kai Breuhahn, Franziska Matthäus
BACKGROUND: The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for detecting significant expression dynamics often fail when the expression dynamics show a large heterogeneity. Moreover, these methods often cannot cope with irregular and sparse measurements...
January 14, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28086747/microrna-based-pan-cancer-diagnosis-and-treatment-recommendation
#13
Nikhil Cheerla, Olivier Gevaert
BACKGROUND: The current state-of-the-art in cancer diagnosis and treatment is not ideal; diagnostic tests are accurate but invasive, and treatments are "one-size fits-all" instead of being personalized. Recently, miRNA's have garnered significant attention as cancer biomarkers, owing to their ease of access (circulating miRNA in the blood) and stability. There have been many studies showing the effectiveness of miRNA data in diagnosing specific cancer types, but few studies explore the role of miRNA in predicting treatment outcome...
January 13, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28086746/mviaeval-a-web-tool-for-comprehensively-evaluating-the-performance-of-a-new-missing-value-imputation-algorithm
#14
Wei-Sheng Wu, Meng-Jhun Jhou
BACKGROUND: Missing value imputation is important for microarray data analyses because microarray data with missing values would significantly degrade the performance of the downstream analyses. Although many microarray missing value imputation algorithms have been developed, an objective and comprehensive performance comparison framework is still lacking. To solve this problem, we previously proposed a framework which can perform a comprehensive performance comparison of different existing algorithms...
January 13, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28077070/scopa-and-meta-scopa-software-for-the-analysis-and-aggregation-of-genome-wide-association-studies-of-multiple-correlated-phenotypes
#15
Reedik Mägi, Yury V Suleimanov, Geraldine M Clarke, Marika Kaakinen, Krista Fischer, Inga Prokopenko, Andrew P Morris
BACKGROUND: Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits...
January 11, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28077065/structure-alignment-based-classification-of-rna-binding-pockets-reveals-regional-rna-recognition-motifs-on-protein-surfaces
#16
Zhi-Ping Liu, Shutang Liu, Ruitang Chen, Xiaopeng Huang, Ling-Yun Wu
BACKGROUND: Many critical biological processes are strongly related to protein-RNA interactions. Revealing the protein structure motifs for RNA-binding will provide valuable information for deciphering protein-RNA recognition mechanisms and benefit complementary structural design in bioengineering. RNA-binding events often take place at pockets on protein surfaces. The structural classification of local binding pockets determines the major patterns of RNA recognition. RESULTS: In this work, we provide a novel framework for systematically identifying the structure motifs of protein-RNA binding sites in the form of pockets on regional protein surfaces via a structure alignment-based method...
January 11, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28077064/an-internet-based-bioinformatics-toolkit-for-plant-biosecurity-diagnosis-and-surveillance-of-viruses-and-viroids
#17
Roberto A Barrero, Kathryn R Napier, James Cunnington, Lia Liefting, Sandi Keenan, Rebekah A Frampton, Tamas Szabo, Simon Bulman, Adam Hunter, Lisa Ward, Mark Whattam, Matthew I Bellgard
BACKGROUND: Detection and preventing entry of exotic viruses and viroids at the border is critical for protecting plant industries trade worldwide. Existing post entry quarantine screening protocols rely on time-consuming biological indicators and/or molecular assays that require knowledge of infecting viral pathogens. Plants have developed the ability to recognise and respond to viral infections through Dicer-like enzymes that cleave viral sequences into specific small RNA products. Many studies reported the use of a broad range of small RNAs encompassing the product sizes of several Dicer enzymes involved in distinct biological pathways...
January 11, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28061750/genomecat-a-versatile-tool-for-the-analysis-and-integrative-visualization-of-dna-copy-number-variants
#18
Katrin Tebel, Vivien Boldt, Anne Steininger, Matthias Port, Grit Ebert, Reinhard Ullmann
BACKGROUND: The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multidimensional data analysis and comparison of patient cohorts are needed to assist in the discrimination of clinically relevant CNVs from others. RESULTS: We developed GenomeCAT, a standalone Java application for the analysis and integrative visualization of CNVs...
January 6, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28061747/gtb-an-online-genome-tolerance-browser
#19
Hashem A Shihab, Mark F Rogers, Michael Ferlaino, Colin Campbell, Tom R Gaunt
BACKGROUND: Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool exists to visualize the predicted tolerance of the genome to mutation, or the similarities between these methods. RESULTS: We present the Genome Tolerance Browser (GTB, http://gtb...
January 6, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28056784/t-recs-rapid-and-large-scale-detection-of-recombination-events-among-different-evolutionary-lineages-of-viral-genomes
#20
Michail Tsimpidis, Georgios Bachoumis, Kalliopi Mimouli, Zaharoula Kyriakopoulou, David L Robertson, Panayotis Markoulatos, Grigoris D Amoutzias
BACKGROUND: Many computational tools that detect recombination in viruses are not adapted for the ongoing genomic revolution. A computational tool is needed, that will rapidly scan hundreds/thousands of genomes or sequence fragments and detect candidate recombination events that may later be further analyzed with more sensitive and specialized methods. RESULTS: T-RECs, a Windows based graphical tool, employs pairwise alignment of sliding windows and can perform (i) genotyping, (ii) clustering of new genomes, (iii) detect recent recombination events among different evolutionary lineages, (iv) manual inspection of detected recombination events by similarity plots and (v) annotation of genomic regions...
January 5, 2017: BMC Bioinformatics
journal
journal
35178
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"