LEADER 06416nam 2200517 450 001 996464421303316 005 20231110215909.0 010 $a3-030-79290-0 035 $a(CKB)5590000000523703 035 $a(MiAaPQ)EBC6665408 035 $a(Au-PeEL)EBL6665408 035 $a(OCoLC)1259437909 035 $a(PPN)259791342 035 $a(EXLCZ)995590000000523703 100 $a20220322d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aComputational advances in bio and medical sciences $e10th international conference, ICCABS 2020, virtual event, December 10-12, 2020, revised selected papers /$fedited by Sumit Kumar Jha [and three others] 210 1$aCham, Switzerland :$cSpringer,$d[2021] 210 4$d©2021 215 $a1 online resource (149 pages) 225 1 $aLecture Notes in Computer Science ;$vv.12686 311 $a3-030-79289-7 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Contents -- Computational Advances in Bio and Medical Sciences -- DNA Read Feature Importance Using Machine Learning for Read Alignment Categories -- 1 Introduction -- 2 Related Work and Motivation -- 3 Methods -- 3.1 Data Acquisition and Read Mapping -- 3.2 Feature and Class Extraction -- 3.3 Machine Learning Methods -- 4 Results -- 4.1 Model Accuracy -- 4.2 Feature Importance -- 4.3 Feature Ranking Similarity Across Different Data -- 4.4 Machine Learning Filter Proof-of-Concept -- 5 Conclusions -- References -- MetaProb 2: Improving Unsupervised Metagenomic Binning with Efficient Reads Assembly Using Minimizers -- 1 Introduction -- 2 Method -- 2.1 Phase 1: Unitig Construction -- 2.2 Phase 2: Community Detection -- 2.3 Phase 3: Species Identification -- 3 Results and Discussion -- 3.1 Datasets Description and Performance Evaluation Metrics -- 3.2 Results -- 4 Conclusions and Future Work -- References -- Computational Study of Action Potential Generation in Urethral Smooth Muscle Cell -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References -- Metabolic Pathway Prediction using Non-negative Matrix Factorization with Improved Precision -- 1 Introduction -- 2 Method -- 2.1 Decomposing the Pathway EC Association Matrix -- 2.2 Community Reconstruction and Multi-label Learning -- 3 Experiments -- 3.1 T1 Golden Data -- 3.2 Three E. coli Data -- 3.3 Mealybug Symbionts Data -- 3.4 CAMI and HOTS Data -- 4 Conclusion -- References -- A Novel Pathway Network Analytics Method Based on Graph Theory -- 1 Introduction -- 2 Methods -- 2.1 Identification of Significantly Enriched Pathways -- 2.2 Construction of a Weighted Network -- 2.3 Identification of Sub-networks -- 2.4 Identification of Important Pathways -- 3 Results and Discussions -- 3.1 Dataset Employed -- 3.2 Outcomes and Relevant Discussions. 327 $a4 Conclusions -- References -- Latent Variable Modelling and Variational Inference for scRNA-seq Differential Expression Analysis -- 1 Introduction -- 2 Methods -- 2.1 ext-ZINBayes -- 2.2 SIENA -- 3 Results -- 4 Conclusion -- References -- Computational Advances for Single-Cell Omics Data Analysis -- Computational Cell Cycle Analysis of Single Cell RNA-Seq Data -- 1 Background and Motivation -- 2 Methods -- 2.1 Datasets -- 2.2 The SC1 Cell Cycle (SC1CC) Analysis Tool -- 3 Results and Discussion -- 3.1 Results on the hESC Dataset -- 3.2 Results on the PBMC Dataset -- 3.3 Results on the -CTLA-4 Dataset -- 3.4 Results on the mHSC Dataset -- 4 Conclusion -- References -- Single-Cell Gene Regulatory Network Analysis Reveals Potential Mechanisms of Action of Antimalarials Against SARS-CoV-2 -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Set -- 2.2 Machine Learning Workflow -- 3 Results and Discussion -- 4 Conclusion -- References -- Computational Advances for Next Generation Sequencing -- RACCROCHE: Ancestral Flowering Plant Chromosomes and Gene Orders Based on Generalized Adjacencies and Chromosomal Gene Co-occurrences -- 1 Introduction -- 2 Methods -- 2.1 Input -- 2.2 The Pipeline -- 2.3 Visualizing and Evaluating the Reconstruction -- 2.4 Ancestral Gene Function -- 3 Reconstruction of Monocot Ancestors -- 3.1 Properties of the Contig Reconstruction -- 3.2 Clustering -- 3.3 Painting the Chromosomes of the Present-Day Genomes -- 3.4 Evaluation -- 3.5 MCScanX Visualization -- 4 Discussions and Conclusions -- A Redistributing Genes from Families Exceeding Upper Size Limits -- B Modes of Contig Construction -- C Matching Contigs to Chromosomes of Extant Genomes -- D Construction of Ancestral Chromosomes -- E Functional Annotation of Ancestral Genes -- References. 327 $aA Fast Word Embedding Based Classifier to Profile Target Gene Databases in Metagenomic Samples -- 1 Introduction -- 2 Methods -- 2.1 Indexing Protein Reference Databases -- 2.2 Prediction of Short Reads -- 2.3 Databases -- 2.4 True Positive Dataset -- 2.5 False Positives Dataset -- 2.6 Time and Memory Profiling -- 2.7 Functional Annotation of Metagenomic Datasets -- 3 Results and Discussion -- 3.1 Detection of True Positive Hits -- 3.2 Detection of False Positives Hits -- 3.3 Time and Memory Usage of MetaMLP -- 3.4 Functional Annotation of Different Environments -- 3.5 Observation of MetaMLP Annotations Against an Extensive Metagenomics Study -- 4 Conclusions -- References -- Clustering Based Identification of SARS-CoV-2 Subtypes -- 1 Background -- 2 Clustering Methods -- 2.1 CliqueSNV Based Clustering -- 2.2 k-modes Clustering -- 2.3 MeShClust -- 2.4 Gap Filling -- 3 Assessment of Clustering Viral Subtypes -- 3.1 Cluster Entropy -- 3.2 Fitness -- 4 Results -- 4.1 Analysis of GISAID Data -- 4.2 Analysis of EMBL-EBI Data -- 5 Conclusions -- References -- Author Index. 410 0$aLecture Notes in Computer Science 606 $aComputers, Special purpose 606 $aMedical informatics$vCongresses 606 $aBioinformatics$vCongresses 615 0$aComputers, Special purpose. 615 0$aMedical informatics 615 0$aBioinformatics 676 $a570.285 702 $aJha$b Sumit Kumar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464421303316 996 $aComputational Advances in Bio and Medical Sciences$92201466 997 $aUNISA