Works matching IS 13674803 AND DT 2020 AND VI 36
Results: 1093
Calibrating variant-scoring methods for clinical decision making.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5709, doi. 10.1093/bioinformatics/btaa943
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Obelisc: an identical-by-descent mapping tool based on SNP streak.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5567, doi. 10.1093/bioinformatics/btaa940
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The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST).
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- Bioinformatics, 2020, v. 36, n. 24, p. 5712, doi. 10.1093/bioinformatics/btaa622
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BERT-GT: cross-sentence n-ary relation extraction with BERT and Graph Transformer.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5678, doi. 10.1093/bioinformatics/btaa1087
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The VCBS superfamily forms a third supercluster of β-propellers that includes tachylectin and integrins.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5618, doi. 10.1093/bioinformatics/btaa1085
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A two-step approach to testing overall effect of gene–environment interaction for multiple phenotypes.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5640, doi. 10.1093/bioinformatics/btaa1083
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Deep neural networks for predicting restricted mean survival times.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5672, doi. 10.1093/bioinformatics/btaa1082
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Accurate, scalable cohort variant calls using DeepVariant and GLnexus.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5582, doi. 10.1093/bioinformatics/btaa1081
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NinimHMDA: neural integration of neighborhood information on a multiplex heterogeneous network for multiple types of human Microbe–Disease association.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5665, doi. 10.1093/bioinformatics/btaa1080
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A non-linear regression method for estimation of gene–environment heritability.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5632, doi. 10.1093/bioinformatics/btaa1079
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Improving circRNA–disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5656, doi. 10.1093/bioinformatics/btaa1077
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Prediction of histone post-translational modifications using deep learning.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5610, doi. 10.1093/bioinformatics/btaa1075
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Identification of sub-Golgi protein localization by use of deep representation learning features.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5600, doi. 10.1093/bioinformatics/btaa1074
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An open-source high-content analysis workflow for CFTR function measurements using the forskolin-induced swelling assay.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5686, doi. 10.1093/bioinformatics/btaa1073
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Predicting Nash equilibria for microbial metabolic interactions.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5649, doi. 10.1093/bioinformatics/btaa1014
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SODA: multi-locus species delimitation using quartet frequencies.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5623, doi. 10.1093/bioinformatics/btaa1010
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VINYL: Variant prIoritizatioN bY survivaL analysis.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5590, doi. 10.1093/bioinformatics/btaa1067
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The COVID-19 Ontology.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5703, doi. 10.1093/bioinformatics/btaa1057
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ClonoMatch: a tool for identifying homologous immunoglobulin and T-cell receptor sequences in large databases.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5695, doi. 10.1093/bioinformatics/btaa1028
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DockIT: a tool for interactive molecular docking and molecular complex construction.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5698, doi. 10.1093/bioinformatics/btaa1059
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cytomapper: an R/Bioconductor package for visualization of highly multiplexed imaging data.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5706, doi. 10.1093/bioinformatics/btaa1061
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glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5701, doi. 10.1093/bioinformatics/btaa1009
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Novel SARS-CoV-2 encoded small RNAs in the passage to humans.
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- Bioinformatics, 2020, v. 36, n. 24, p. 5571, doi. 10.1093/bioinformatics/btaa1002
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ECCB2020: the 19th European Conference on Computational Biology.
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- Bioinformatics, 2020, v. 36, p. i569, doi. 10.1093/bioinformatics/btaa979
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Ensembling graph attention networks for human microbe–drug association prediction.
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- Bioinformatics, 2020, v. 36, p. i779, doi. 10.1093/bioinformatics/btaa891
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A general near-exact k-mer counting method with low memory consumption enables de novo assembly of 106× human sequence data in 2.7 hours.
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- Bioinformatics, 2020, v. 36, p. i625, doi. 10.1093/bioinformatics/btaa890
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Geometricus represents protein structures as shape-mers derived from moment invariants.
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- Bioinformatics, 2020, v. 36, p. i718, doi. 10.1093/bioinformatics/btaa839
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MirCure: a tool for quality control, filter and curation of microRNAs of animals and plants.
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- Bioinformatics, 2020, v. 36, p. i618, doi. 10.1093/bioinformatics/btaa889
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SCIM: universal single-cell matching with unpaired feature sets.
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- Bioinformatics, 2020, v. 36, p. i919, doi. 10.1093/bioinformatics/btaa843
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Supervised learning on phylogenetically distributed data.
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- Bioinformatics, 2020, v. 36, p. i895, doi. 10.1093/bioinformatics/btaa842
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A Siamese neural network model for the prioritization of metabolic disorders by integrating real and simulated data.
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- Bioinformatics, 2020, v. 36, p. i787, doi. 10.1093/bioinformatics/btaa841
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A neuro-evolution approach to infer a Boolean network from time-series gene expressions.
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- Bioinformatics, 2020, v. 36, p. i762, doi. 10.1093/bioinformatics/btaa840
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Inferring signaling pathways with probabilistic programming.
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- Bioinformatics, 2020, v. 36, p. i822, doi. 10.1093/bioinformatics/btaa861
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DeepCDR: a hybrid graph convolutional network for predicting cancer drug response.
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- Bioinformatics, 2020, v. 36, p. i911, doi. 10.1093/bioinformatics/btaa822
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The effect of kinship in re-identification attacks against genomic data sharing beacons.
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- Bioinformatics, 2020, v. 36, p. i903, doi. 10.1093/bioinformatics/btaa821
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Using a GTR+Γ substitution model for dating sequence divergence when stationarity and time-reversibility assumptions are violated.
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- Bioinformatics, 2020, v. 36, p. i884, doi. 10.1093/bioinformatics/btaa820
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Batch equalization with a generative adversarial network.
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- Bioinformatics, 2020, v. 36, p. i875, doi. 10.1093/bioinformatics/btaa819
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Matrix (factorization) reloaded: flexible methods for imputing genetic interactions with cross-species and side information.
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- Bioinformatics, 2020, v. 36, p. i866, doi. 10.1093/bioinformatics/btaa818
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FastSK: fast sequence analysis with gapped string kernels.
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- Bioinformatics, 2020, v. 36, p. i857, doi. 10.1093/bioinformatics/btaa817
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SCHNEL: scalable clustering of high dimensional single-cell data.
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- Bioinformatics, 2020, v. 36, p. i849, doi. 10.1093/bioinformatics/btaa816
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Enhancing statistical power in temporal biomarker discovery through representative shapelet mining.
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- Bioinformatics, 2020, v. 36, p. i840, doi. 10.1093/bioinformatics/btaa815
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Dementia key gene identification with multi-layered SNP-gene-disease network.
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- Bioinformatics, 2020, v. 36, p. i831, doi. 10.1093/bioinformatics/btaa814
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FBA reveals guanylate kinase as a potential target for antiviral therapies against SARS-CoV-2.
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- Bioinformatics, 2020, v. 36, p. i813, doi. 10.1093/bioinformatics/btaa813
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Probabilistic graphlets capture biological function in probabilistic molecular networks.
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- Bioinformatics, 2020, v. 36, p. i804, doi. 10.1093/bioinformatics/btaa812
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Padhoc: a computational pipeline for pathway reconstruction on the fly.
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- Bioinformatics, 2020, v. 36, p. i795, doi. 10.1093/bioinformatics/btaa811
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Feasible-metabolic-pathway-exploration technique using chemical latent space.
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- Bioinformatics, 2020, v. 36, p. i770, doi. 10.1093/bioinformatics/btaa809
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APOD: accurate sequence-based predictor of disordered flexible linkers.
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- Bioinformatics, 2020, v. 36, p. i754, doi. 10.1093/bioinformatics/btaa808
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New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics.
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- Bioinformatics, 2020, v. 36, p. i745, doi. 10.1093/bioinformatics/btaa807
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PROBselect: accurate prediction of protein-binding residues from proteins sequences via dynamic predictor selection.
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- Bioinformatics, 2020, v. 36, p. i735, doi. 10.1093/bioinformatics/btaa806
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GRaSP: a graph-based residue neighborhood strategy to predict binding sites.
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- Bioinformatics, 2020, v. 36, p. i726, doi. 10.1093/bioinformatics/btaa805
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