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BMC Bioinformatics

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https://www.readbyqxmd.com/read/28810903/a-neural-network-multi-task-learning-approach-to-biomedical-named-entity-recognition
#1
Gamal Crichton, Sampo Pyysalo, Billy Chiu, Anna Korhonen
BACKGROUND: Named Entity Recognition (NER) is a key task in biomedical text mining. Accurate NER systems require task-specific, manually-annotated datasets, which are expensive to develop and thus limited in size. Since such datasets contain related but different information, an interesting question is whether it might be possible to use them together to improve NER performance. To investigate this, we develop supervised, multi-task, convolutional neural network models and apply them to a large number of varied existing biomedical named entity datasets...
August 15, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28810826/improving-fold-resistance-prediction-of-hiv-1-against-protease-and-reverse-transcriptase-inhibitors-using-artificial-neural-networks
#2
Olivier Sheik Amamuddy, Nigel T Bishop, Özlem Tastan Bishop
BACKGROUND: Drug resistance in HIV treatment is still a worldwide problem. Predicting resistance to antiretrovirals (ARVs) before starting any treatment is important. Prediction accuracy is essential, as low-accuracy predictions increase the risk of prescribing sub-optimal drug regimens leading to patients developing resistance sooner. Artificial Neural Networks (ANNs) are a powerful tool that would be able to assist in drug resistance prediction. In this study, we constrained the dataset to subtype B, sacrificing generalizability for a higher predictive performance, and demonstrated that the predictive quality of the ANN regression models have definite improvement for most ARVs...
August 15, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28797233/full-l1-regularized-traction-force-microscopy-over-whole-cells
#3
Alejandro Suñé-Auñón, Alvaro Jorge-Peñas, Rocío Aguilar-Cuenca, Miguel Vicente-Manzanares, Hans Van Oosterwyck, Arrate Muñoz-Barrutia
BACKGROUND: Traction Force Microscopy (TFM) is a widespread technique to estimate the tractions that cells exert on the surrounding substrate. To recover the tractions, it is necessary to solve an inverse problem, which is ill-posed and needs regularization to make the solution stable. The typical regularization scheme is given by the minimization of a cost functional, which is divided in two terms: the error present in the data or data fidelity term; and the regularization or penalty term...
August 10, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28797229/odg-omics-database-generator-a-tool-for-generating-querying-and-analyzing-multi-omics-comparative-databases-to-facilitate-biological-understanding
#4
Joseph Guhlin, Kevin A T Silverstein, Peng Zhou, Peter Tiffin, Nevin D Young
BACKGROUND: Rapid generation of omics data in recent years have resulted in vast amounts of disconnected datasets without systemic integration and knowledge building, while individual groups have made customized, annotated datasets available on the web with few ways to link them to in-lab datasets. With so many research groups generating their own data, the ability to relate it to the larger genomic and comparative genomic context is becoming increasingly crucial to make full use of the data...
August 10, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28797226/network-design-and-analysis-for-multi-enzyme-biocatalysis
#5
Lisa Katharina Blaß, Christian Weyler, Elmar Heinzle
BACKGROUND: As more and more biological reaction data become available, the full exploration of the enzymatic potential for the synthesis of valuable products opens up exciting new opportunities but is becoming increasingly complex. The manual design of multi-step biosynthesis routes involving enzymes from different organisms is very challenging. To harness the full enzymatic potential, we developed a computational tool for the directed design of biosynthetic production pathways for multi-step catalysis with in vitro enzyme cascades, cell hydrolysates and permeabilized cells...
August 10, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28793860/local-sequence-and-sequencing-depth-dependent-accuracy-of-rna-seq-reads
#6
Guoshuai Cai, Shoudan Liang, Xiaofeng Zheng, Feifei Xiao
BACKGROUND: Many biases and spurious effects are inherent in RNA-seq technology, resulting in a non-uniform distribution of sequencing read counts for each base position in a gene. Therefore, a base-level strategy is required to model the non-uniformity. Also, the properties of sequencing read counts can be leveraged to achieve a more precise estimation of the mean and variance of measurement. RESULTS: In this study, we aimed to unveil the effects on RNA-seq accuracy from multiple factors and develop accurate modeling of RNA-seq reads in comparison...
August 9, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28789639/cipher-a-flexible-and-extensive-workflow-platform-for-integrative-next-generation-sequencing-data-analysis-and-genomic-regulatory-element-prediction
#7
Carlos Guzman, Iván D'Orso
BACKGROUND: Next-generation sequencing (NGS) approaches are commonly used to identify key regulatory networks that drive transcriptional programs. Although these technologies are frequently used in biological studies, NGS data analysis remains a challenging, time-consuming, and often irreproducible process. Therefore, there is a need for a comprehensive and flexible workflow platform that can accelerate data processing and analysis so more time can be spent on functional studies. RESULTS: We have developed an integrative, stand-alone workflow platform, named CIPHER, for the systematic analysis of several commonly used NGS datasets including ChIP-seq, RNA-seq, MNase-seq, DNase-seq, GRO-seq, and ATAC-seq data...
August 8, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28784111/a-nonparametric-bayesian-method-of-translating-machine-learning-scores-to-probabilities-in-clinical-decision-support
#8
Brian Connolly, K Bretonnel Cohen, Daniel Santel, Ulya Bayram, John Pestian
BACKGROUND: Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approaches that calibrate the ML output with a likelihood scale. Current state-of-the-art calibration methods are generally accurate and applicable to many ML models, but improved granularity and accuracy of such methods would increase the information available for clinical decision making...
August 7, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28784090/repliscan-a-tool-for-classifying-replication-timing-regions
#9
Gregory J Zynda, Jawon Song, Lorenzo Concia, Emily E Wear, Linda Hanley-Bowdoin, William F Thompson, Matthew W Vaughn
BACKGROUND: Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing. RESULTS: To accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures...
August 7, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28774263/evaluation-of-high-throughput-isomir-identification-tools-illuminating-the-early-isomirome-of-tribolium-castaneum
#10
Daniel Amsel, Andreas Vilcinskas, André Billion
BACKGROUND: MicroRNAs carry out post-transcriptional gene regulation in animals by binding to the 3' untranslated regions of mRNAs, causing their degradation or translational repression. MicroRNAs influence many biological functions, and dysregulation can therefore disrupt development or even cause death. High-throughput sequencing and the mining of animal small RNA data has shown that microRNA genes can yield differentially expressed isoforms, known as isomiRs. Such isoforms are particularly relevant during early development, and the extension or truncation of the 5' end can change the profile of mRNA targets compared to the original mature sequence...
August 3, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28774262/parallel-multiple-instance-learning-for-extremely-large-histopathology-image-analysis
#11
Yan Xu, Yeshu Li, Zhengyang Shen, Ziwei Wu, Teng Gao, Yubo Fan, Maode Lai, Eric I-Chao Chang
BACKGROUND: Histopathology images are critical for medical diagnosis, e.g., cancer and its treatment. A standard histopathology slice can be easily scanned at a high resolution of, say, 200,000×200,000 pixels. These high resolution images can make most existing imaging processing tools infeasible or less effective when operated on a single machine with limited memory, disk space and computing power. RESULTS: In this paper, we propose an algorithm tackling this new emerging "big data" problem utilizing parallel computing on High-Performance-Computing (HPC) clusters...
August 3, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28764645/correcting-nucleotide-specific-biases-in-high-throughput-sequencing-data
#12
Jeremy R Wang, Bryan Quach, Terrence S Furey
BACKGROUND: High-throughput sequence (HTS) data exhibit position-specific nucleotide biases that obscure the intended signal and reduce the effectiveness of these data for downstream analyses. These biases are particularly evident in HTS assays for identifying regulatory regions in DNA (DNase-seq, ChIP-seq, FAIRE-seq, ATAC-seq). Biases may result from many experiment-specific factors, including selectivity of DNA restriction enzymes and fragmentation method, as well as sequencing technology-specific factors, such as choice of adapters/primers and sample amplification methods...
August 1, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28764644/variable-selection-for-disease-progression-models-methods-for-oncogenetic-trees-and-application-to-cancer-and-hiv
#13
Katrin Hainke, Sebastian Szugat, Roland Fried, Jörg Rahnenführer
BACKGROUND: Disease progression models are important for understanding the critical steps during the development of diseases. The models are imbedded in a statistical framework to deal with random variations due to biology and the sampling process when observing only a finite population. Conditional probabilities are used to describe dependencies between events that characterise the critical steps in the disease process. Many different model classes have been proposed in the literature, from simple path models to complex Bayesian networks...
August 1, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28750623/l1kdeconv-an-r-package-for-peak-calling-analysis-with-lincs-l1000-data
#14
Zhao Li, Jin Li, Peng Yu
BACKGROUND: LINCS L1000 is a high-throughput technology that allows gene expression measurement in a large number of assays. However, to fit the measurements of ~1000 genes in the ~500 color channels of LINCS L1000, every two landmark genes are designed to share a single channel. Thus, a deconvolution step is required to infer the expression values of each gene. Any errors in this step can be propagated adversely to the downstream analyses. RESULTS: We presented a LINCS L1000 data peak calling R package l1kdeconv based on a new outlier detection method and an aggregate Gaussian mixture model (AGMM)...
July 27, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28750606/assessing-the-model-transferability-for-prediction-of-transcription-factor-binding-sites-based-on-chromatin-accessibility
#15
Sheng Liu, Cristina Zibetti, Jun Wan, Guohua Wang, Seth Blackshaw, Jiang Qian
BACKGROUND: Computational prediction of transcription factor (TF) binding sites in different cell types is challenging. Recent technology development allows us to determine the genome-wide chromatin accessibility in various cellular and developmental contexts. The chromatin accessibility profiles provide useful information in prediction of TF binding events in various physiological conditions. Furthermore, ChIP-Seq analysis was used to determine genome-wide binding sites for a range of different TFs in multiple cell types...
July 27, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28743252/quantification-of-tumour-evolution-and-heterogeneity-via-bayesian-epiallele-detection
#16
James E Barrett, Andrew Feber, Javier Herrero, Miljana Tanic, Gareth A Wilson, Charles Swanton, Stephan Beck
BACKGROUND: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called 'epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. RESULTS: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour...
July 25, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28738841/identifying-and-mitigating-batch-effects-in-whole-genome-sequencing-data
#17
Jennifer A Tom, Jens Reeder, William F Forrest, Robert R Graham, Julie Hunkapiller, Timothy W Behrens, Tushar R Bhangale
BACKGROUND: Large sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data...
July 24, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28738824/visibiome-an-efficient-microbiome-search-engine-based-on-a-scalable-distributed-architecture
#18
Syafiq Kamarul Azman, Muhammad Zohaib Anwar, Andreas Henschel
BACKGROUND: Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. RESULTS: We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges...
July 24, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28738814/an-extended-model-of-vesicle-fusion-at-the-plasma-membrane-to-estimate-protein-lateral-diffusion-from-tirf-microscopy-images
#19
Antoine Basset, Patrick Bouthemy, Jérôme Boulanger, François Waharte, Jean Salamero, Charles Kervrann
BACKGROUND: Characterizing membrane dynamics is a key issue to understand cell exchanges with the extra-cellular medium. Total internal reflection fluorescence microscopy (TIRFM) is well suited to focus on the late steps of exocytosis at the plasma membrane. However, it is still a challenging task to quantify (lateral) diffusion and estimate local dynamics of proteins. RESULTS: A new model was introduced to represent the behavior of cargo transmembrane proteins during the vesicle fusion to the plasma membrane at the end of the exocytosis process...
July 24, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28732468/nogoa-predicting-noisy-go-annotations-using-evidences-and-sparse-representation
#20
Guoxian Yu, Chang Lu, Jun Wang
BACKGROUND: Gene Ontology (GO) is a community effort to represent functional features of gene products. GO annotations (GOA) provide functional associations between GO terms and gene products. Due to resources limitation, only a small portion of annotations are manually checked by curators, and the others are electronically inferred. Although quality control techniques have been applied to ensure the quality of annotations, the community consistently report that there are still considerable noisy (or incorrect) annotations...
July 21, 2017: BMC Bioinformatics
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