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https://www.readbyqxmd.com/read/29773825/consistent-prediction-of-go-protein-localization
#1
Flavio E Spetale, Debora Arce, Flavia Krsticevic, Pilar Bulacio, Elizabeth Tapia
The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automated GO-CC annotation of proteins suffer from the inconsistency of individual GO-CC term predictions. Here, we present FGGA-CC+ , a class of hierarchical graph-based classifiers for the consistent GO-CC annotation of protein coding genes at the subcellular compartment or macromolecular complex levels...
May 17, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29771663/applications-of-deep-learning-and-reinforcement-learning-to-biological-data
#2
Mufti Mahmud, Mohammed Shamim Kaiser, Amir Hussain, Stefano Vassanelli
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29769331/temporal-transcriptional-logic-of-dynamic-regulatory-networks-underlying-nitrogen-signaling-and-use-in-plants
#3
Kranthi Varala, Amy Marshall-Colón, Jacopo Cirrone, Matthew D Brooks, Angelo V Pasquino, Sophie Léran, Shipra Mittal, Tara M Rock, Molly B Edwards, Grace J Kim, Sandrine Ruffel, W Richard McCombie, Dennis Shasha, Gloria M Coruzzi
This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets...
May 16, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29769297/mechanistic-models-versus-machine-learning-a-fight-worth-fighting-for-the-biological-community
#4
REVIEW
Ruth E Baker, Jose-Maria Peña, Jayaratnam Jayamohan, Antoine Jérusalem
Ninety per cent of the world's data have been generated in the last 5 years ( Machine learning: the power and promise of computers that learn by example Report no. DES4702. Issued April 2017. Royal Society). A small fraction of these data is collected with the aim of validating specific hypotheses. These studies are led by the development of mechanistic models focused on the causality of input-output relationships. However, the vast majority is aimed at supporting statistical or correlation studies that bypass the need for causality and focus exclusively on prediction...
May 2018: Biology Letters
https://www.readbyqxmd.com/read/29768460/a-guide-to-automated-apoptosis-detection-how-to-make-sense-of-imaging-flow-cytometry-data
#5
Dennis Pischel, Jörn H Buchbinder, Kai Sundmacher, Inna N Lavrik, Robert J Flassig
Imaging flow cytometry is a powerful experimental technique combining the strength of microscopy and flow cytometry to enable high-throughput characterization of cell populations on a detailed microscopic scale. This approach has an increasing importance for distinguishing between different cellular phenotypes such as proliferation, cell division and cell death. In the course of undergoing these different pathways, each cell is characterized by a high amount of properties. This makes it hard to filter the most relevant information for cell state discrimination...
2018: PloS One
https://www.readbyqxmd.com/read/29766490/emotional-hyper-reactivity-and-cardiometabolic-risk-in-remitted-bipolar-patients-a-machine-learning-approach
#6
A A Dargél, F Roussel, S Volant, B Etain, R Grant, J-M Azorin, K M'Bailara, F Bellivier, T Bougerol, J-P Kahn, P Roux, V Aubin, P Courtet, M Leboyer, F Kapczinski, C Henry
OBJECTIVE: Remitted bipolar disorder (BD) patients frequently present with chronic mood instability and emotional hyper-reactivity, associated with poor psychosocial functioning and low-grade inflammation. We investigated emotional hyper-reactivity as a dimension for characterization of remitted BD patients, and clinical and biological factors for identifying those with and without emotional hyper-reactivity. METHOD: A total of 635 adult remitted BD patients, evaluated in the French Network of Bipolar Expert Centers from 2010-2015, were assessed for emotional reactivity using the Multidimensional Assessment of Thymic States...
May 15, 2018: Acta Psychiatrica Scandinavica
https://www.readbyqxmd.com/read/29765080/distinguishing-mirtrons-from-canonical-mirnas-with-data-exploration-and-machine-learning-methods
#7
Grzegorz Rorbach, Olgierd Unold, Bogumil M Konopka
Mirtrons are non-canonical microRNAs encoded in introns the biogenesis of which starts with splicing. They are not processed by Drosha and enter the canonical pathway at the Exportin-5 level. Mirtrons are much less evolutionary conserved than canonical miRNAs. Due to the differences, canonical miRNA predictors are not applicable to mirtron prediction. Identification of differences is important for designing mirtron prediction algorithms and may help to improve the understanding of mirtron functioning. So far, only simple, single-feature comparisons were reported...
May 15, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29764379/identification-of-usual-interstitial-pneumonia-pattern-using-rna-seq-and-machine-learning-challenges-and-solutions
#8
Yoonha Choi, Tiffany Ting Liu, Daniel G Pankratz, Thomas V Colby, Neil M Barth, David A Lynch, P Sean Walsh, Ganesh Raghu, Giulia C Kennedy, Jing Huang
BACKGROUND: We developed a classifier using RNA sequencing data that identifies the usual interstitial pneumonia (UIP) pattern for the diagnosis of idiopathic pulmonary fibrosis. We addressed significant challenges, including limited sample size, biological and technical sample heterogeneity, and reagent and assay batch effects. RESULTS: We identified inter- and intra-patient heterogeneity, particularly within the non-UIP group. The models classified UIP on transbronchial biopsy samples with a receiver-operating characteristic area under the curve of ~ 0...
May 9, 2018: BMC Genomics
https://www.readbyqxmd.com/read/29763495/early-response-of-fibroblasts-and-epithelial-cells-to-pink-shaded-anodized-dental-implant-abutments-an-in-vitro-study
#9
Federico Mussano, Tullio Genova, Marco Laurenti, Elisa Zicola, Luca Munaron, Paola Rivolo, Pietro Mandracci, Stefano Carossa
PURPOSE: This research aimed to assess whether pink-shaded anodized surfaces could enhance the adhesion of soft tissue cells compared with untreated machined titanium surfaces. MATERIALS AND METHODS: Two types of Ti-Al-V titanium samples were prepared: machined titanium (Ti) and anodized titanium (AnoTi). The microstructure was studied by means of a scanning electron microscope. X-ray photoelectron spectroscopy (XPS) was carried out as well. The wetting properties were investigated by the sessile drop technique with water and diiodomethane...
May 2018: International Journal of Oral & Maxillofacial Implants
https://www.readbyqxmd.com/read/29760087/-pseudomonas-aeruginosa-transcriptome-during-human-infection
#10
Daniel M Cornforth, Justine L Dees, Carolyn B Ibberson, Holly K Huse, Inger H Mathiesen, Klaus Kirketerp-Møller, Randy D Wolcott, Kendra P Rumbaugh, Thomas Bjarnsholt, Marvin Whiteley
Laboratory experiments have uncovered many basic aspects of bacterial physiology and behavior. After the past century of mostly in vitro experiments, we now have detailed knowledge of bacterial behavior in standard laboratory conditions, but only a superficial understanding of bacterial functions and behaviors during human infection. It is well-known that the growth and behavior of bacteria are largely dictated by their environment, but how bacterial physiology differs in laboratory models compared with human infections is not known...
May 14, 2018: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/29759983/high-throughput-discovery-of-functional-disordered-regions-investigation-of-transactivation-domains
#11
Charles Nj Ravarani, Tamara Y Erkina, Greet De Baets, Daniel C Dudman, Alexandre M Erkine, M Madan Babu
Over 40% of proteins in any eukaryotic genome encode intrinsically disordered regions (IDRs) that do not adopt defined tertiary structures. Certain IDRs perform critical functions, but discovering them is non-trivial as the biological context determines their function. We present IDR-Screen, a framework to discover functional IDRs in a high-throughput manner by simultaneously assaying large numbers of DNA sequences that code for short disordered sequences. Functionality-conferring patterns in their protein sequence are inferred through statistical learning...
May 14, 2018: Molecular Systems Biology
https://www.readbyqxmd.com/read/29758660/mechanical-transduction-via-a-single-soft-polymer
#12
Ruizheng Hou, Nan Wang, Weizhu Bao, Zhisong Wang
Molecular machines from biology and nanotechnology often depend on soft structures to perform mechanical functions, but the underlying mechanisms and advantages or disadvantages over rigid structures are not fully understood. We report here a rigorous study of mechanical transduction along a single soft polymer based on exact solutions to the realistic three-dimensional wormlike-chain model and augmented with analytical relations derived from simpler polymer models. The results reveal surprisingly that a soft polymer with vanishingly small persistence length below a single chemical bond still transduces biased displacement and mechanical work up to practically significant amounts...
April 2018: Physical Review. E
https://www.readbyqxmd.com/read/29758261/annotating-diseases-using-human-phenotype-ontology-improves-prediction-of-disease-associated-long-non-coding-rnas
#13
Duc-Hau Le, Lan T M Dao
Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitation in experimentally identifying disease-lncRNA associations, computational methods have been proposed as a powerful tool to predict such associations. These methods are usually based on the similarities between diseases or lncRNAs since it was reported that similar diseases are associated with functionally similar lncRNAs...
May 11, 2018: Journal of Molecular Biology
https://www.readbyqxmd.com/read/29755261/spider-assemblages-associated-with-different-crop-stages-of-irrigated-rice-agroecosystems-from-eastern-uruguay
#14
Leticia Bao, Juaquín Ginella, Mónica Cadenazzi, Enrique A Castiglioni, Sebastián Martínez, Luis Casales, María P Caraballo, Álvaro Laborda, Miguel Simo
The rice crop and associated ecosystems constitute a rich mosaic of habitats that preserve a rich biological diversity. Spiders are an abundant and successful group of natural predators that are considered efficient in the biocontrol of the major insect pests in agroecosystems. Spider diversity in different stages of the rice crop growth from eastern Uruguay was analysed. Field study was developed on six rice farms with rotation system with pasture, installed during intercropping stage as cover crop. Six rice crops distributed in three locations were sampled with pitfall and entomological vaccum suction machine...
2018: Biodiversity Data Journal
https://www.readbyqxmd.com/read/29750902/machine-learning-in-chemoinformatics-and-drug-discovery
#15
REVIEW
Yu-Chen Lo, Stefano E Rensi, Wen Torng, Russ B Altman
Chemoinformatics is an established discipline focusing on extracting, processing and extrapolating meaningful data from chemical structures. With the rapid explosion of chemical 'big' data from HTS and combinatorial synthesis, machine learning has become an indispensable tool for drug designers to mine chemical information from large compound databases to design drugs with important biological properties. To process the chemical data, we first reviewed multiple processing layers in the chemoinformatics pipeline followed by the introduction of commonly used machine learning models in drug discovery and QSAR analysis...
May 8, 2018: Drug Discovery Today
https://www.readbyqxmd.com/read/29750795/multiclass-classification-for-skin-cancer-profiling-based-on-the-integration-of-heterogeneous-gene-expression-series
#16
Juan Manuel Gálvez, Daniel Castillo, Luis Javier Herrera, Belén San Román, Olga Valenzuela, Francisco Manuel Ortuño, Ignacio Rojas
Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited...
2018: PloS One
https://www.readbyqxmd.com/read/29737976/uniform-resolution-of-compact-identifiers-for-biomedical-data
#17
Sarala M Wimalaratne, Nick Juty, John Kunze, Greg Janée, Julie A McMurry, Niall Beard, Rafael Jimenez, Jeffrey S Grethe, Henning Hermjakob, Maryann E Martone, Tim Clark
Most biomedical data repositories issue locally-unique accessions numbers, but do not provide globally unique, machine-resolvable, persistent identifiers for their datasets, as required by publishers wishing to implement data citation in accordance with widely accepted principles. Local accessions may however be prefixed with a namespace identifier, providing global uniqueness. Such "compact identifiers" have been widely used in biomedical informatics to support global resource identification with local identifier assignment...
May 8, 2018: Scientific Data
https://www.readbyqxmd.com/read/29735903/pharmaceutical-machine-learning-virtual-high-throughput-screens-identifying-promising-and-economical-small-molecule-inhibitors-of-complement-factor-c1s
#18
Jonathan J Chen, Lyndsey N Schmucker, Donald P Visco
When excessively activated, C1 is insufficiently regulated, which results in tissue damage. Such tissue damage causes the complement system to become further activated to remove the resulting tissue damage, and a vicious cycle of activation/tissue damage occurs. Current Food and Drug Administration approved treatments include supplemental recombinant C1 inhibitor, but these are extremely costly and a more economical solution is desired. In our work, we have utilized an existing data set of 136 compounds that have been previously tested for activity against C1...
May 7, 2018: Biomolecules
https://www.readbyqxmd.com/read/29735804/volatile-fingerprinting-of-i-pseudomonas-aeruginosa-i-and-respiratory-syncytial-virus-infection-in-an-i-in-vitro-i-cystic-fibrosis-co-infection-model
#19
Giorgia Purcaro, Christiaan Rees, Jeffrey A Melvin, Jennifer M Bomberg, Jane E Hill
Volatile molecules in exhaled breath represent potential biomarkers in the setting of infectious diseases, particularly those affecting the respiratory tract. In particular, Pseudomonas aeruginosa is a critically-important respiratory pathogen in specific subsets of the population, such as those with cystic fibrosis. Infections caused by P. aeruginosa can be particularly problematic when co-infection with respiratory syncytial virus (RSV) occurs, as this is correlated with the establishment of chronic P. aeruginosa infection...
May 8, 2018: Journal of Breath Research
https://www.readbyqxmd.com/read/29735743/the-substrate-specificity-of-eukaryotic-cytosolic-chaperonin-cct
#20
REVIEW
Keith R Willison
The cytosolic chaperonin CCT (chaperonin containing TCP-1) is an ATP-dependent double-ring protein machine mediating the folding of members of the eukaryotic cytoskeletal protein families. The actins and tubulins are obligate substrates of CCT because they are completely dependent on CCT activity to reach their native states. Genetic and proteomic analysis of the CCT interactome in the yeast Saccharomyces cerevisiae revealed a CCT network of approximately 300 genes and proteins involved in many fundamental biological processes...
June 19, 2018: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
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