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Journal of Computational Biology: a Journal of Computational Molecular Cell Biology

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https://read.qxmd.com/read/30681362/deep-reinforcement-learning-and-simulation-as-a-path-toward-precision-medicine
#1
Brenden K Petersen, Jiachen Yang, Will S Grathwohl, Chase Cockrell, Claudio Santiago, Gary An, Daniel M Faissol
Traditionally, precision medicine involves classifying patients to identify subpopulations that respond favorably to specific therapeutics. We pose precision medicine as a dynamic feedback control problem, where treatment administered to a patient is guided by measurements taken during the course of treatment. We consider sepsis, a life-threatening condition in which dysregulation of the immune system causes tissue damage. We leverage an existing simulation of the innate immune response to infection and apply deep reinforcement learning (DRL) to discover an adaptive personalized treatment policy that specifies effective multicytokine therapy to simulated sepsis patients based on systemic measurements...
January 25, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30676086/bounds-on-identification-of-genome-evolution-pacemakers
#2
Sagi Snir
Several studies have pointed out that the tight correlation between genes' evolutionary rate is better explained by a model denoted as the Universal PaceMaker (UPM) rather than by a simple rate constancy as manifested by the classical hypothesis of molecular clock (MC). Under UPM, each gene is associated with a single pacemaker (PM) and varies its evolutionary rate according to this PM ticks. Hence, the relative rates of all genes associated with the same PM remain nearly constant, whereas the absolute rates can change arbitrarily according to the PM ticks...
January 24, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30653353/a-boltzmann-sampler-for-1-pairs-with-double-filtration
#3
Christopher Barrett, Qijun He, Fenix W Huang, Christian M Reidys
Recently, a framework considering RNA sequences and their RNA secondary structures as pairs led to some information-theoretic perspectives on how the semantics encoded in RNA sequences can be inferred. This pairing arises naturally from the energy model of RNA secondary structures. Fixing the sequence in the pairing produces the RNA energy landscape, whose partition function was discovered by McCaskill. Dually, fixing the structure induces the energy landscape of sequences. The latter has been considered originally for designing more efficient inverse folding algorithms and subsequently enhanced by facilitating the sampling of sequences...
January 17, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30653343/regression-based-network-estimation-for-high-dimensional-genetic-data
#4
Kyu Min Lee, Minhyeok Lee, Junhee Seok, Sung Won Han
Given the continuous advancement in genome sequencing technology, large volumes of gene expression data can be easily obtained. However, the corresponding increase in genetic information necessitates adoption of a new approach for network estimation. Data dimensions increase with the progress in genome sequencing technology, thereby making it difficult to estimate gene networks by causing multicollinearity. Furthermore, such a problem also occurs when hub nodes exist, where gene networks are known to have regulator genes that can be interpreted as hub nodes...
January 17, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30653336/micloud-a-plug-n-play-extensible-on-premises-bioinformatics-cloud-for-seamless-execution-of-complex-next-generation-sequencing-data-analysis-pipelines
#5
Baekdoo Kim, Thahmina Ali, Changsu Dong, Carlos Lijeron, Raja Mazumder, Claudia Wultsch, Konstantinos Krampis
The availability of low-cost small-factor sequencers, such as the Illumina MiSeq, MiniSeq, or iSeq, have paved the way for democratizing genomics sequencing, providing researchers in minority universities with access to the technology that was previously only affordable by institutions with large core facilities. However, these instruments are not bundled with software for performing bioinformatics data analysis, and the data analysis can be the main bottleneck for independent laboratories or even small clinical facilities that consider adopting genomic sequencing for medical applications...
January 17, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30638400/computing-nonoverlapping-inversion-distance-between-two-strings-in-linear-average-time
#6
Xiaodong Wang, Lei Wang
Biological events like inversions are not automatically detected by the usual alignment algorithms. Alignment with inversions does not have a known polynomial time algorithm and Schöniger and Waterman introduced a simplification of the alignment problem with nonoverlapping inversions, where all regions will not be allowed to overlap. They presented an \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\usepackage{upgreek}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} $${ \cal O} ( {n^6} )$$ \end{document} algorithm to compute nonoverlapping inversion distance between two strings of length n...
January 14, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30638394/robust-sample-specific-stability-selection-with-effective-error-control
#7
Heewon Park, Makoto Yamada, Seiya Imoto, Satoru Miyano
Identifying individual characteristics is a crucial issue in personalized genome research. To effectively identify sample-specific characteristics, we propose a novel strategy called robust sample-specific stability selection. Although stability selection shows effective feature selection results and has attractive theoretical property (i.e., per-family error rate control), the method's results are sensitive to the value of the regularization parameter because the method performs feature selection based only on the particular parameter value that maximizes the selection probability...
January 14, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30624962/a-service-oriented-platform-for-approximate-bayesian-computation-in-population-genetics
#8
Roberto Solar, Victor Sepulveda, Alonso Inostrosa-Psijas, Oscar Rojas, Veronica Gil-Costa, Mauricio Marin
Approximate Bayesian computation (ABC) is a useful technique developed for solving Bayesian inference without explicitly requiring a likelihood function. In population genetics, it is widely used to extract part of the information about the evolutionary history of genetic data. The ABC compares the summary statistics computed on simulated and observed data sets. Typically, a forward-in-time approach is used to simulate the genetic material of a population starting from an initial ancestral population and following the evolution of the individuals by advancing generation by generation under various demographic and genetic forces...
January 9, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30624960/cell-modeling-based-on-bubbles-with-weighted-membranes
#9
Yuandi Wang, Qingmei Wen, Zhigang Zhou, Nanjun Yan
Mathematicization for cell modeling provides an effective tool to verify the biological theory, and the existing research mainly focuses on the description of cell structures. This article then addresses the pattern question of cell division or morphogenesis by means of bubble model with weighted membranes. In this study, we show that cell shapes including intersection angles at junction points depend on weights on membranes. For convenience, adhesion and contractile force are considered together as a factor in construction of patterning model...
January 9, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30624954/compression-of-phylogenetic-networks-and-algorithm-for-the-tree-containment-problem
#10
Andreas D M Gunawan, Hongwei Yan, Louxin Zhang
Rooted phylogenetic networks are rooted acyclic digraphs. They are used to model complex evolution where hybridization, recombination, and other reticulation events play a role. A rigorous definition of network compression is introduced on the basis of recent studies of relationships between cluster, tree, and rooted phylogenetic networks. The concept reveals new connections between well-studied network classes, including tree-child networks and reticulation-visible networks. It also enables us to define a new class of networks for which the cluster containment problem is solvable in linear time...
January 9, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30615482/index-db-the-indian-exome-reference-database-phase-i
#11
Husayn Ahmed P, Vidhya V, Ravi Prabhakar More, Biju Viswanath, Sanjeev Jain, Mahendra S Rao, Odity Mukherjee
Deep sequencing-based genetic mapping has greatly enhanced the ability to catalog variants with plausible disease association. Confirming how these identified variants contribute to specific disease conditions, across human populations, poses the next challenge. Differential selection pressure may impact the frequency of genetic variations, and thus detection of association with disease conditions, across populations. To understand genotype to phenotype correlations, it thus becomes important to first understand the spectrum of genetic variation within a population by creating a reference map...
January 7, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30614735/hcolondb-a-database-for-human-colon-cancer-research
#12
Xiaodan Mao, Yichen Xu, Zhenran Jiang
HColonDB (Human Colon cancer Database) is an important database which integrates genes, pathways, networks, drugs, and other information related to colon cancer. The purpose of the database is to provide a platform for the systematic research of colon cancer. The relationships between genes and pathways, genes and networks, and networks and pathways are obtained from the database KEGG. Furthermore, the information of the drugs used to treat colon cancer is available in HColonDB, which is collected and organized from DrugBank and PubChem database...
January 7, 2019: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30585743/deepsnp-an-end-to-end-deep-neural-network-with-attention-based-localization-for-breakpoint-detection-in-single-nucleotide-polymorphism-array-genomic-data
#13
Hamid Eghbal-Zadeh, Lukas Fischer, Niko Popitsch, Florian Kromp, Sabine Taschner-Mandl, Teresa Gerber, Eva Bozsaky, Peter F Ambros, Inge M Ambros, Gerhard Widmer, Bernhard A Moser
Clinical decision-making in cancer and other diseases relies on timely and cost-effective genome-wide testing. Classical bioinformatic algorithms, such as Rawcopy, can support genomic analysis by calling genomic breakpoints and copy-number variations (CNVs), but often require manual data curation, which is error prone, time-consuming, and thus substantially increasing costs of genomic testing and hampering timely delivery of test results to the treating physician. We aimed to investigate whether deep learning algorithms can be used to learn from genome-wide single-nucleotide polymorphism array (SNPa) data and improve state-of-the-art algorithms...
December 26, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30585742/search-effectiveness-in-nonredundant-sequence-databases-assessments-and-solutions
#14
Qingyu Chen, Xiuzhen Zhang, Yu Wan, Justin Zobel, Karin Verspoor
Duplicate sequence records-that is, records having similar or identical sequences-are a challenge in search of biological sequence databases. They significantly increase database search time and can lead to uninformative search results containing similar sequences. Sequence clustering methods have been used to address this issue to group similar sequences into clusters. These clusters form a nonredundant database consisting of representatives (one record per cluster) and members (the remaining records in a cluster)...
December 26, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30570348/molecular-dynamics-studies-of-histo-blood-group-antigen-blocking-human-immunoglobulin-a-antibody-and-escape-mechanism-in-noroviruses-upon-mutation
#15
Muslum Yildiz, Abdulkadir Kocak
Norovirus is the causing agent of acute gastroenteritis disease globally. Efforts in developing therapeutics against virus infection mostly fail due to emergence of drug resistance that is a consequence of presence of high mutation rates in virus genome during virus' life cycle. In this study, we computationally analyzed the affinity of a drug target, wild type VP1 envelope protein and its three variants to a therapeutic antibody FAB5I2. We have found that mutations break important hydrogen bonds and cause high fluctuations in residues that form VP1-FAB5I2 complex interface...
December 20, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30562062/directional-association-measurement-in-contingency-tables-genomic-case
#16
Monika Piwowar, Tomasz KuŁaga
Analysis of large data sets is currently a major challenge. Strong efforts are being undertaken to tackle this problem by developing new methods or modifying existing ones. The Z association method is a new method for describing directional association in contingency tables. It allows to arbitrarily group categories for each of the two variables, for which the contingency table is analyzed. The Z coefficient was calculated on a sample data set with gene mutations in different cancer types. Results showed some association with both gene mutations and annotation groups...
December 18, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30547672/in-silico-characterization-of-b-cell-and-t-cell-epitopes-for-subunit-vaccine-design-of-salmonella-typhi-pgte-a-molecular-dynamics-simulation-approach
#17
Gopinath Samykannu, Princy Vijayababu, Christian Bharathi Antonyraj, Perumal Perumal, Sundarabaalaji Narayanan, Syed Ibrahim Basheer Ahamed, Jeyakumar Natarajan
Typhoid fever is an acute illness in humans, caused by Salmonella typhi, a gram-negative bacterium. Outer membrane proteins of S. typhi have strong potential for its use in the development of subunit vaccine against typhoid. In the current study, peptide-based subunit vaccine was constructed from outer membrane protease E (PgtE) against S. typhi. B cell and T cell epitopes were identified at fold level with a validated three-dimensional modeled structure. T cell epitopes from PgtE (IHPDTSANY) have 99.5% binding to a maximum number of major histocompatibility complex class I and class II alleles...
December 14, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30526005/autoencoding-topographic-factors
#18
Antonio Moretti, Andrew Stirn, Gabriel Marks, Itsik Pe'er
Topographic factor models separate overlapping signals into latent spatial functions to identify correlation structure across observations. These methods require the underlying structure to be held fixed and are not robust to deviations commonly found across images. We present autoencoding topographic factors, a novel variational inference scheme, to decompose irregular observations on a lattice into a superposition of low-rank sources. By exploiting recent developments in variational autoencoders, we replace fixed sources with a nonlinear mapping that parameterizes an unnormalized distribution on the lattice...
December 7, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30526025/three-dimensional-embryonic-image-segmentation-and-registration-based-on-shape-index-and-ellipsoid-fitting-method
#19
Sihai Yang, Xianhua Han, Yenwei Chen
Quantitative analysis based on three-dimensional differential interference contrast (DIC) images is currently the mainstream in analyzing gene functions involved in early cell fate specifications. Segmentation and registration are the two most important steps in analysis. Many image segmentation methods have poor performance on embryonic DIC images because of the interference of egg shells, blurs, and nonuniform intensity background. A novel segmentation method is presented based on the shape index (SI) of local intensity variation in DIC images...
December 5, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
https://read.qxmd.com/read/30517025/a-de-novo-robust-clustering-approach-for-amplicon-based-sequence-data
#20
Alexandre Bazin, Didier Debroas, Engelbert Mephu Nguifo
When analyzing microbial communities, an active and computational challenge concerns the categorization of 16S rRNA gene sequences into operational taxonomic units (OTUs). Established clustering tools use a one pass algorithm to tackle high number of gene sequences and produce OTUs in reasonable time. However, all of the current tools are based on a crisp clustering approach, where a gene sequence is assigned to one cluster. The weak quality of the output compared with more complex clustering algorithms forces the user to postprocess the obtained OTUs...
December 5, 2018: Journal of Computational Biology: a Journal of Computational Molecular Cell Biology
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