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Computational biology

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https://www.readbyqxmd.com/read/28346487/ml2motif-reliable-extraction-of-discriminative-sequence-motifs-from-learning-machines
#1
Marina M-C Vidovic, Marius Kloft, Klaus-Robert Müller, Nico Görnitz
High prediction accuracies are not the only objective to consider when solving problems using machine learning. Instead, particular scientific applications require some explanation of the learned prediction function. For computational biology, positional oligomer importance matrices (POIMs) have been successfully applied to explain the decision of support vector machines (SVMs) using weighted-degree (WD) kernels. To extract relevant biological motifs from POIMs, the motifPOIM method has been devised and showed promising results on real-world data...
2017: PloS One
https://www.readbyqxmd.com/read/28346484/a-neighborhood-wide-association-study-nwas-example-of-prostate-cancer-aggressiveness
#2
Shannon M Lynch, Nandita Mitra, Michelle Ross, Craig Newcomb, Karl Dailey, Tara Jackson, Charnita M Zeigler-Johnson, Harold Riethman, Charles C Branas, Timothy R Rebbeck
PURPOSE: Cancer results from complex interactions of multiple variables at the biologic, individual, and social levels. Compared to other levels, social effects that occur geospatially in neighborhoods are not as well-studied, and empiric methods to assess these effects are limited. We propose a novel Neighborhood-Wide Association Study(NWAS), analogous to genome-wide association studies(GWAS), that utilizes high-dimensional computing approaches from biology to comprehensively and empirically identify neighborhood factors associated with disease...
2017: PloS One
https://www.readbyqxmd.com/read/28346469/computational-identifying-and-characterizing-circular-rnas-and-their-associated-genes-in-hepatocellular-carcinoma
#3
Yan Li, Yongcheng Dong, Ziyan Huang, Qifan Kuang, Yiming Wu, Yizhou Li, Menglong Li
Hepatocellular carcinoma (HCC) is currently still a major factor leading to death, lacking of reliable biomarkers. Therefore, deep understanding the pathogenesis for HCC is of great importance. The emergence of circular RNA (circRNA) provides a new way to study the pathogenesis of human disease. Here, we employed the prediction tool to identify circRNAs based on RNA-seq data. Then, to investigate the biological function of the circRNA, the candidate circRNAs were associated with the protein-coding genes (PCGs) by GREAT...
2017: PloS One
https://www.readbyqxmd.com/read/28346087/pubchem-bioassay
#4
Yanli Wang, Tiejun Cheng, Stephen H Bryant
High-throughput screening (HTS) is now routinely conducted for drug discovery by both pharmaceutical companies and screening centers at academic institutions and universities. Rapid advance in assay development, robot automation, and computer technology has led to the generation of terabytes of data in screening laboratories. Despite the technology development toward HTS productivity, fewer efforts were devoted to HTS data integration and sharing. As a result, the huge amount of HTS data was rarely made available to the public...
January 1, 2017: SLAS Discov
https://www.readbyqxmd.com/read/28345935/targeting-self-binding-peptides-as-a-novel-strategy-to-regulate-protein-activity-and-function-a-case-study-on-the-proto-oncogene-tyrosine-protein-kinase-c-src
#5
Zhengya Bai, Shasha Hou, Shilei Zhang, Zhongyan Li, Peng Zhou
Previously, we have reported a new biomolecular phenomenon spanning between protein folding and binding, termed as self-binding peptides (SBPs), where a short peptide segment in monomeric protein functions as molecular switch by dynamically binding to/unbinding from its cognate domain in the monomer (Yang C, Zhang S, He P, Wang C, Huang J, Zhou P. Self-binding peptides: folding or binding? J. Chem. Inf. MODEL: 2015, 55: 329-342). Here, we attempt to raise the SBP as a new class of druggable targets to regulate the biological activity and function of proteins...
March 27, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28344853/snap-a-general-purpose-network-analysis-and-graph-mining-library
#6
Jure Leskovec, Rok Sosič
Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate large networks, only a limited number of tools are available for this task. Here, we describe Stanford Network Analysis Platform (SNAP), a general-purpose, high-performance system that provides easy to use, high-level operations for analysis and manipulation of large networks...
October 2016: ACM Transactions on Intelligent Systems and Technology
https://www.readbyqxmd.com/read/28344638/the-feasibility-of-genome-scale-biological-network-inference-using-graphics-processing-units
#7
Raghuram Thiagarajan, Amir Alavi, Jagdeep T Podichetty, Jason N Bazil, Daniel A Beard
Systems research spanning fields from biology to finance involves the identification of models to represent the underpinnings of complex systems. Formal approaches for data-driven identification of network interactions include statistical inference-based approaches and methods to identify dynamical systems models that are capable of fitting multivariate data. Availability of large data sets and so-called 'big data' applications in biology present great opportunities as well as major challenges for systems identification/reverse engineering applications...
2017: Algorithms for Molecular Biology: AMB
https://www.readbyqxmd.com/read/28344603/isobio-software-biological-dose-distribution-and-biological-dose-volume-histogram-from-physical-dose-conversion-using-linear-quadratic-linear-model
#8
Tanwiwat Jaikuna, Phatchareewan Khadsiri, Nisa Chawapun, Suwit Saekho, Ekkasit Tharavichitkul
PURPOSE: To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model. MATERIAL AND METHODS: The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system...
February 2017: Journal of Contemporary Brachytherapy
https://www.readbyqxmd.com/read/28344341/functional-variomics-and-network-perturbation-connecting-genotype-to-phenotype-in-cancer
#9
REVIEW
Song Yi, Shengda Lin, Yongsheng Li, Wei Zhao, Gordon B Mills, Nidhi Sahni
Proteins interact with other macromolecules in complex cellular networks for signal transduction and biological function. In cancer, genetic aberrations have been traditionally thought to disrupt the entire gene function. It has been increasingly appreciated that each mutation of a gene could have a subtle but unique effect on protein function or network rewiring, contributing to diverse phenotypic consequences across cancer patient populations. In this Review, we discuss the current understanding of cancer genetic variants, including the broad spectrum of mutation classes and the wide range of mechanistic effects on gene function in the context of signalling networks...
March 27, 2017: Nature Reviews. Genetics
https://www.readbyqxmd.com/read/28344201/stenotic-bicuspid-and-tricuspid-aortic-valves%C3%A3-micro-computed-tomography-and-biological-indices-of-calcification
#10
Piotr Mazur, Ewa Wypasek, Bogusław Gawęda, Dorota Sobczyk, Przemysław Kapusta, Joanna Natorska, Krzysztof Piotr Malinowski, Jacek Tarasiuk, Maciej Bochenek, Sebastian Wroński, Katarzyna Chmielewska, Bogusław Kapelak, Anetta Undas
BACKGROUND: Valve calcification is well estimated by ex-vivo micro-computed tomography (micro-CT). The objective of this study was to investigate the associations between micro-CT findings and biological indices of calcification in aortic stenosis (AS), as well as differences between bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV).Methods and Results:Aortic valves and plasma were obtained from patients undergoing valve surgery. Valves were dissected and underwent micro-CT, genetic analyses, and calcium content assessment...
March 24, 2017: Circulation Journal: Official Journal of the Japanese Circulation Society
https://www.readbyqxmd.com/read/28344110/toward-a-systematic-exploration-of-nano-bio-interactions
#11
REVIEW
Xue Bai, Fang Liu, Yin Liu, Cong Li, Shenqing Wang, Hongyu Zhou, Wenyi Wang, Hao Zhu, Dave Winkler, Bing Yan
Many studies of nanomaterials make non-systematic alterations of nanoparticle physicochemical properties. Given the immense size of the property space for nanomaterials, such approaches are not very useful in elucidating fundamental relationships between inherent physicochemical properties of these materials and their interactions with, and effects on, biological systems. Data driven artificial intelligence methods such as machine learning algorithms have proven highly effective in generating models with good predictivity and some degree of interpretability...
March 24, 2017: Toxicology and Applied Pharmacology
https://www.readbyqxmd.com/read/28341288/establishing-the-structures-within-populations-of-models
#12
REVIEW
Philip M Gemmell
As computational biology matures as a field, increasing attention is being paid to the relation of computational models to their target. One aspect of this is addressing how computational models can appropriately reproduce the variation seen in experimental data, with one solution being to use populations of models united by a common set of equations (the framework), with each individual member of the population (each model) possessing its own unique set of equation parameters. These model populations are then calibrated and validated against experimental data, and as a whole reproduce the experimentally observed variation...
March 21, 2017: Progress in Biophysics and Molecular Biology
https://www.readbyqxmd.com/read/28341061/vmat-plus-a-few-computer-optimized-non-coplanar-imrt-beams-vmat-tested-for-liver-sbrt
#13
Abdul Wahab M Sharfo, Maarten L P Dirkx, Sebastiaan Breedveld, Alejandra Méndez Romero, Ben J M Heijmen
PURPOSE: To propose a novel treatment approach, designated VMAT+, involving addition of <5 IMRT beams with computer-optimized non-coplanar orientations to VMAT, and evaluate it for liver Stereotactic Body Radiation Therapy (SBRT). VMAT+ is investigated as an alternative for (1) coplanar VMAT and (2) multi-beam non-coplanar treatment. METHODS/MATERIALS: For fifteen patients with liver metastases, VMAT+ plans were compared with (1) dual-arc VMAT and (2) 25-beam, non-coplanar treatment with computer-optimized beam orientations (25-NCP)...
March 22, 2017: Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology
https://www.readbyqxmd.com/read/28340624/medecom-discovery-and-quantification-of-latent-components-of-heterogeneous-methylomes
#14
Pavlo Lutsik, Martin Slawski, Gilles Gasparoni, Nikita Vedeneev, Matthias Hein, Jörn Walter
It is important for large-scale epigenomic studies to determine and explore the nature of hidden confounding variation, most importantly cell composition. We developed MeDeCom as a novel reference-free computational framework that allows the decomposition of complex DNA methylomes into latent methylation components and their proportions in each sample. MeDeCom is based on constrained non-negative matrix factorization with a new biologically motivated regularization function. It accurately recovers cell-type-specific latent methylation components and their proportions...
March 24, 2017: Genome Biology
https://www.readbyqxmd.com/read/28340582/optimisation-of-an-exemplar-oculomotor-model-using-multi-objective-genetic-algorithms-executed-on-a-gpu-cpu-combination
#15
Eleftherios Avramidis, Ozgur E Akman
BACKGROUND: Parameter optimisation is a critical step in the construction of computational biology models. In eye movement research, computational models are increasingly important to understanding the mechanistic basis of normal and abnormal behaviour. In this study, we considered an existing neurobiological model of fast eye movements (saccades), capable of generating realistic simulations of: (i) normal horizontal saccades; and (ii) infantile nystagmus - pathological ocular oscillations that can be subdivided into different waveform classes...
March 24, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28342987/circular-rnas-and-cancer
#16
Jun He, Qichao Xie, Hailin Xu, Jiantian Li, Yongsheng Li
Circular RNAs (circRNAs) are a type of non-coding RNA molecules that lack a 5'-terminal cap and 3'-terminal poly A tail. A large number of circRNAs have been identified through biological experiments, computational methods and high-throughput sequencing. CircRNA sequence composition determines if a given circRNA is exonic, intronic or retained-intronic. CircRNAs are more abundant and stable than linear mRNAs, and their expression is both step- and location-specific. CircRNAs mediate transcriptional and post-transcriptional regulation of gene and protein expression...
March 22, 2017: Cancer Letters
https://www.readbyqxmd.com/read/28339468/pbmda-a-novel-and-effective-path-based-computational-model-for-mirna-disease-association-prediction
#17
Zhu-Hong You, Zhi-An Huang, Zexuan Zhu, Gui-Ying Yan, Zheng-Wei Li, Zhenkun Wen, Xing Chen
In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases...
March 24, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28338692/computational-design-of-self-assembling-cyclic-protein-homo-oligomers
#18
Jorge A Fallas, George Ueda, William Sheffler, Vanessa Nguyen, Dan E McNamara, Banumathi Sankaran, Jose Henrique Pereira, Fabio Parmeggiani, T J Brunette, Duilio Cascio, Todd R Yeates, Peter Zwart, David Baker
Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein-protein interface. This method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces...
April 2017: Nature Chemistry
https://www.readbyqxmd.com/read/28337450/scalable-data-mining-algorithms-in-computational-biology-and-biomedicine
#19
EDITORIAL
Quan Zou, Dariusz Mrozek, Qin Ma, Yungang Xu
No abstract text is available yet for this article.
2017: BioMed Research International
https://www.readbyqxmd.com/read/28336911/2d-hybrid-analysis-approach-for-building-three-dimensional-atomic-model-by-electron-microscopy-image-matching
#20
Atsushi Matsumoto, Naoyuki Miyazaki, Junichi Takagi, Kenji Iwasaki
In this study, we develop an approach termed "2D hybrid analysis" for building atomic models by image matching from electron microscopy (EM) images of biological molecules. The key advantage is that it is applicable to flexible molecules, which are difficult to analyze by 3DEM approach. In the proposed approach, first, a lot of atomic models with different conformations are built by computer simulation. Then, simulated EM images are built from each atomic model. Finally, they are compared with the experimental EM image...
March 23, 2017: Scientific Reports
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