1. Bioinformatics research and applications : 16th International Symposium, ISBRA 2020, Moscow, Russia, December 1-4, 2020, Proceedings 
- ISBRA (Conference) (16th : 2020 : Moscow, Russia)
- Cham, Switzerland : Springer, 
- Book — 1 online resource Digital: text file.PDF.
- Mitochondrial Haplogroup Assignment for High-Throughput Sequencing Data from Single Individual and Mixed DNA Samples.- Signet Ring Cell Detection with Classi cation Reinforcement Detection Network.- SPOC: Identification of Drug Targets in Biological Networks via Set Preference Output Control.- Identification of a novel compound heterozygous variant in NBAS causing bone fragility by the type of osteogenesis imperfecta.- Isoform-disease association prediction by data fusion.- EpIntMC: Detecting Epistatic Interactions using Multiple Clusterings.- Improving Metagenomic Classi cation using discriminative k-mers from sequencing data.- Dilated-DenseNet For Macromolecule Classifi cation In Cryo-electron Tomography.- Ess-NEXG: Predict Essential Proteins by Constructing a Weighted.- Protein Interaction Network based on Node Embedding and XGBoost.- mapAlign: an efficient approach for mapping and aligning long reads to reference genomes.- Functional Evolutionary Modeling Exposes Overlooked Protein-Coding Genes Involved in Cancer.- Testing the Agreement of Trees with Internal Labels.- SVLR: Genome Structure Variant Detection Using Long Read Sequencing Data.- De novo prediction of drug-target interaction via Laplacian regularized Schatten-p norm minimization.- Diagnosis of ASD from rs-fMRIs based on brain dynamic networks.- miRNA-Disease Associations Prediction Based on Negative Sample Selection and Multi-layer Perceptron.- Checking Phylogenetic Decisiveness in Theory and in Practice.- TNet: Phylogeny-Based Inference of Disease Transmission Networks Using Within-Host Strain Diversity.- Cancer breakpoint hotspots versus individual breakpoints prediction by machine learning models.- Integer Linear Programming Formulation for the Uni ed DuplicationLoss-Coalescence Model.- In silico-guided discovery of potential HIV-1 entry inhibitors mimicking bNAb
- N6: virtual screening, docking, molecular dynamics, and post-molecular modeling analysis.- Learning Structural Genetic Information via Graph Neural Embedding.- A New Network-based Tool to Analyse Competing Endogenous RNAs.- Deep Ensemble models for 16S Ribosomal Gene Classification.- Search for tandem repeats in the rst chromosome from the rice genome.- Deep Learning approach with rotate-shift invariant input to predict protein homodimer structure.- Development of a Neural Network-Based Approach for Prediction of Potential HIV-1 Entry Inhibitors Using Deep Learning and Molecular Modeling Methods.- In Silico Design and Evaluation of Novel Triazole-Based Compounds as Promising Drug Candidates Against Breast Cancer.- Identification of essential genes with NemoPro le and various machine learning models.- NemoLib: Network Motif Libraries for network motif detection and analysis.- Estimating enzyme participation in metabolic pathways for microbial communities from RNA-seq data.- Identication of Virus-Receptor Interactions based on Network Enhancement and Similarity.- Enhanced functional pathway annotations for differentially expressed gene clusters.- Automated Detection of Sleep Apnea from Abdominal Respiratory Signal using Hilbert-Huang Transform.- Na/K-ATPase glutathionylation: in silico modeling of reaction mechanisms.- HiChew: a tool for TAD clustering in embryogenesis.- Generation of Hi-C maps from DNA sequence data using Deep Learning.- S
- C1: A Tool for Interactive Web-Based Single Cell RNA-Seq Data Analysis.- Quantitative analysis of the dynamics of maternal gradients in the early Drosophila embryo.- Atom Tracking Using Cayley Graphs.- SPOC: Identification of Drug Targets in Biological Networks via Set Preference Output Control.- Identification of a novel compound heterozygous variant in NBAS causing bone fragility by the type of osteogenesis imperfecta. .
- (source: Nielsen Book Data)
(source: Nielsen Book Data)