Biocomputing 2010 - Proceedings of the Pacific Symposium |
Autore | Russ B Altman |
Pubbl/distr/stampa | World Scientific Publishing Co, 2009 |
Descrizione fisica | viii, 487 p. : ill. (some col.) |
Disciplina | 572.8 |
Altri autori (Persone) |
AltmanRuss
DunkerA. Keith <1943-> (Alan Keith) HunterLawrence <1961-> |
Soggetto topico |
Bioinformatics
Genomics |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN |
1-282-76350-4
9786612763502 981-4295-29-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Computational challenges in comparative genomics. Session introduction / Bernard Moret ... [et al.]. Accurate taxonomic assignment of short pyrosequencing reads / José C. Clemente , Jesper Jansson, Gabriel Valiente. Benchmarking BLAST accuracy of genus/phyla classification of metagenomic reads / Steven D. Essinger, Gail L. Rosen. Guided genome halving : provably optimal solutions provide good insights into the preduplication ancestral genome of Saccharomyces cerevisiae / Haris Gavranovic, Eric Tannier. A practical algorithm for estimation of the maximum likelihood ancestral reconstruction error / Glenn Hickey, Mathieu Blanchette. Optimization methods for selecting founder populations for captive breeding of endangered species / Webb Miller ... [et al.] -- Computational studies of non-coding RNAs. Session introduction / Rolf Backofen ... [et al.]. RNA structural segmentation / Ivan Dotu ... [et al.]. RNAz 2.0 : improved noncoding RNA detection / Andreas R. Gruber ... [et al.]. Identification and classification of small RNAs in transcriptome sequence data / D. Langenberger ... [et al.]. Improvement of structure conservation index with centroid estimators / Yohei Okada, Kengo Sato, Yasubumi Sakakibara. Dynamic programming algorithms for RNA structure prediction with binding sites / Unyanee Poolsap, Yuki Kato, Tatsuya Akutsu. An algorithm for the energy barrier problem without pseudoknots and temporary arcs / Chris Thachuk ... [et al.] -- Dynamics of biological networks. Session introduction / Tanya Y. Berger-Wolf ... [et al.]. Local optimization for global alignment of protein interaction networks / Leonid Chindelevitch, Chung-Shou Liao, Bonnie Berger. Identification of coordinately dysregulated subnetworks in complex phenotypes / Salim A. Chowdhury, Mehmet Koyuturk. Subspace differential coexpression analysis : problem definition and a general approach / Gang Fang ... [et al.]. Estimation of protein and domain interactions in the switching motility system of Myxococcus xanthus ... [et al.]. Exploring biological network dynamics with ensembles of graph partitions / Saket Navlakha, Carl Kingsford. Geometric evolutionary dynamics of protein interaction networks / Natasa Przulj ... [et al.]. The steady states and dynamics of Urokinase-mediated plasmin activation / Lakshmi Venkatraman ... [et al.] -- Multi-resolution modeling of biological macromolecules. Session introduction / Samuel Flores ... [et al.]. Multi-resolution approach for interactively locating functionally linked ion binding sites by steering small molecules into electrostatic potential maps using a haptic device / Olivier Delalande ... [et al.]. Predicting RNA structure by multiple template homology modeling / Samuel C. Flores ... [et al.]. Constructing multi-resolution Markov State Models (MSMs) to elucidate RNA hairpin folding mechanisms / Xuhui Huang ... [et al.]. Multiscale dynamics of macromolecules using normal mode langevin / Jesus A. Izaguirre, Christopher R. Sweet, Vijay S. Pande. Insights into the intra-ring subunit order of TriC/CCT : structural and evolutionary analysis / Nir Kalisman, Michael Levitt. "Cross-graining :" Efficient multi-scale simulation via Markov state models / Peter Kasson, Vijay Pande. Toward understanding allosteric signaling mechanisms in the ATPase domain of molecular chaperones / Ying Liu, Ivet Bahar. 3D-blast : 3D protein structure alignment, comparison, and classification using spherical polar Fourier correlations / Lazaros Mavridis. David W. Ritchie. Structural prediction of protein-RNA interaction by computational docking with propensity-based statistical potentials / Laura Pérez-Cano ... [et al.] -- Personal genomics. Session introduction / Can Alkan ... [et al.]. Improving the prediction of pharmacogenes using text-derived gene-drug relationships / Yael Garten, Nicholas P. Tatonetti, Russ B. Altman. Finding unique filter sets in PLATO : a precursor to efficient interaction analysis in GWAS data / Benjamin J. Grady ... [et al.]. Enabling personal genomics with an explicit test of epistasis / Casey S. Greene ... [et al.]. Loss of post-translational modification sites in disease / Shuyan Li ... [et al.]. Detecting genome-wide haplotype polymorphism by combined use of mendelian constraints and local population structure / Xin Li, Yixuan Chen, Jing Li. Sequence Feature Variant Type (SFVT) analysis of the HLA genetic association in juvenile idiopathic arthritis / Glenys Thomson ... [et al.]. Cokgen : a software for the identification of rare copy number variation from SNP microarrays / Gökhan Yavas ... [et al.] -- Reverse engineering and synthesis of biomolecular systems. Session introduction / Gil Alterovitz ... [et al.]. Co-design in synthetic biology : a system-level analysis of the development of an environmental sensing device / David A. Ball ... [et al.]. Critical analysis of transcriptional and post-transcriptional regulatory networks in multiple myeloma / Marta Biasiolo ... [et al.]. A computational model of gene expression in an inducible synthetic circuit / Francesca Ceroni, Simone Furini, Silvio Cavalcanti. Retrovirus HTLV-1 gene circuit : a potential oscillator for eukaryotes / Alberto Corradin ... [et al.]. Emulsion based selection of T7 promoters of varying activity / Eric A. Davidson ... [et al.]. Clustering context-specific gene regulatory networks / Archana Ramesh ... [et al.]. Writing and compiling code into biochemistry / Adam Shea ... [et al.]. Synthesis of pharmacokinetic pathways through knowledge acquisition and automated reasoning / Luis Tari ... [et al.] -- Workshops. In silico biology / Richard Goldstein ... [et al.]. Genomic standards consortium workshop : Metagenomics, Metadata and Metaanalysis (M3) / Peter Sterk ... [et al.]. Extraction of genotype-phenotype-drug relationships from text : from entity recognition to bioinformatics application / Adrien Coulet ... [et al.]. |
Record Nr. | UNINA-9910346696203321 |
Russ B Altman | ||
World Scientific Publishing Co, 2009 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Biocomputing 2011 : Proceedings of the Pacific Symposium |
Autore | Altman Russ |
Pubbl/distr/stampa | Singapore, : World Scientific Publishing Company, 2010 |
Descrizione fisica | 1 online resource (500 p.) |
Disciplina | 574.0151 |
Altri autori (Persone) |
DunkerA. Keith <1943-> (Alan Keith)
HunterLawrence <1961-> |
Soggetto topico |
Biology -- Computer simulation -- Congresses
Biology -- Mathematical models -- Congresses Molecular biology -- Computer simulation -- Congresses Molecular biology -- Mathematical models -- Congresses |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN |
1-283-14526-X
9786613145260 981-4335-05-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
PREFACE; CONTENTS; INTEGRATIVE -OMICS FOR TRANSLATIONAL SCIENCE; TOWARDS INTEGRATIVE GENE PRIORITIZATION IN ALZHEIMER'S DISEASE; SYSTEMS BIOLOGY ANALYSES OF GENE EXPRESSION AND GENOME WIDEASSOCIATION STUDY DATA IN OBSTRUCTIVE SLEEP APNEA; FINDING MOST LIKELY HAPLOTYPES IN GENERAL PEDIGREESTHROUGH PARALLEL SEARCH WITH DYNAMIC LOAD BALANCING; DYNAMIC, MULTI-LEVEL NETWORK MODELS OF CLINICAL TRIALS; MINING FUNCTIONALLY RELEVANT GENE SETS FOR ANALYZINGPHYSIOLOGICALLY NOVEL CLINICAL EXPRESSION DATA; GENOTYPE PHENOTYPE MAPPING IN RNA VIRUSES - DISJUNCTIVENORMAL FORM LEARNING
GENOME-WIDE ASSOCIATION MAPPING AND RARE ALLELES: FROMPOPULATION GENOMICS TO PERSONALIZED MEDICINEAN APPLICATION AND EMPIRICAL COMPARISON OF STATISTICAL ANALYSISMETHODS FOR ASSOCIATING RARE VARIANTS TO A COMPLEX PHENOTYPE; HAPLOTYPE PHASING BY MULTI-ASSEMBLY OF SHAREDHAPLOTYPES: PHASE-DEPENDENT INTERACTIONS BETWEEN RARE VARIANTS; AN EVALUATION OF POWER TO DETECT LOW-FREQUENCY VARIANTASSOCIATIONS USING ALLELE-MATCHING TESTS THAT ACCOUNTFOR UNCERTAINTY; PENALIZED REGRESSION FOR GENOME-WIDE ASSOCIATIONSCREENING OF SEQUENCE DATA; MICROBIOME STUDIES: PSB 2011 SPECIAL SESSION INTRODUCTION ESTIMATING THE NUMBER OF SPECIES WITH CATCHALLA FRAMEWORK FOR ANALYSIS OF METAGENOMIC SEQUENCING DATA; VISUALIZATION AND STATISTICAL COMPARISONS OF MICROBIALCOMMUNITIES USING R PACKAGES ON PHYLOCHIP DATA; HUMAN MICROBIOME VISUALIZATION USING 3D TECHNOLOGY; COMPARING BACTERIAL COMMUNITIES INFERRED FROM 16S rRNA GENE SEQUENCING AND SHOTGUN METAGENOMICS; MULTI-SCALE MODELLING OF BIOSYSTEMS: FROM MOLECULAR TOMESOCALE; COMPUTATIONAL GENERATION INHIBITOR-BOUND CONFORMERS OF P38 MAPKINASE AND COMPARISON WITH EXPERIMENTS MOLECULAR DYNAMICS SIMULATIONS OF THE FULL TRIPLE HELICALREGION OF COLLAGEN TYPE I PROVIDE AN ATOMIC SCALE VIEW OF THEPROTEIN'S REGIONAL HETEROGENEITYSTRUCTURAL INSIGHTS INTO PRE-TRANSLOCATION RIBOSOME MOTIONS; NEW CONFORMATIONAL SEARCH METHOD USING GENETICALGORITHM AND KNOT THEORY FOR PROTEINS; PERSONAL GENOMICS; THE REFERENCE HUMAN GENOME DEMONSTRATES HIGH RISK OF TYPE 1DIABETES AND OTHER DISORDERS; MATCHING CANCER GENOMES TO ESTABLISHED CELL LINESFOR PERSONALIZED ONCOLOGY USE OF BIOLOGICAL KNOWLEDGE TO INFORM THE ANALYSIS OF GENE-GENEINTERACTIONS INVOLVED IN MODULATING VIROLOGIC FAILURE WITHEFAVIRENZ-CONTAINING TREATMENT REGIMENS IN ART-NAÏVE ACTG CLINICALTRIALS PARTICVISUAL INTEGRATION OF RESULTS FROM A LARGE DNA BIOBANK (BIOVU)USING SYNTHESIS-VIEW; MULTIVARIATE ANALYSIS OF REGULATORY SNPS: EMPOWERING PERSONALGENOMICS BY CONSIDERING CIS-EPISTASIS AND HETEROGENEITY; HAPLOTYPE INFERENCE FROM SHORT SEQUENCE READS USING APOPULATION GENEALOGICAL HISTORY MODEL; REVERSE ENGINEERING AND SYNTHESIS OF BIOMOLECULAR SYSTEMS; BINARY COUNTING WITH CHEMICAL REACTIONS DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELINGFOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS |
Record Nr. | UNINA-9910346695803321 |
Altman Russ | ||
Singapore, : World Scientific Publishing Company, 2010 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Biocomputing 2018 - Proceedings Of The Pacific Symposium |
Autore | Altman Russ B |
Pubbl/distr/stampa | World Scientific Publishing Co, 2017 |
Descrizione fisica | 1 online resource (649 pages) |
Altri autori (Persone) |
DunkerA. Keith <1943-> (Alan Keith)
HunterLawrence <1961-> RitchieMarylyn D MurrayTiffany A KleinTeri E |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN | 981-323-553-5 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Altri titoli varianti | Biocomputing 2018 |
Record Nr. | UNINA-9910346695003321 |
Altman Russ B | ||
World Scientific Publishing Co, 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Biocomputing 2019 - Proceedings Of The Pacific Symposium |
Autore | Altman Russ B |
Pubbl/distr/stampa | World Scientific Publishing Co, 2018 |
Descrizione fisica | 1 online resource (471 pages) |
Altri autori (Persone) |
DunkerA. Keith <1943-> (Alan Keith)
HunterLawrence <1961-> RitchieMarylyn D MurrayTiffany A KleinTeri E |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN |
981-327-982-6
981-327-981-8 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- PATTERN RECOGNITION IN BIOMEDICAL DATA: CHALLENGES IN PUTTING BIG DATA TO WORK -- Session introduction -- Introduction -- References -- Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes -- 1. Introduction -- 2. Methods -- 2.1. Source Code -- 2.2. Data Source -- 2.3. Data Selection and Preprocessing -- 2.3.1. Reference ICD9 Example -- 2.3.2. Real Member Analyses -- 2.4. Poincaré Embeddings -- 2.5. Processing and Evaluating Embeddings -- 3. Results -- 3.1. ICD9 Hierarchy Evaluation -- 3.2. Poincaré Embeddings on 10 Million Members -- 3.3. Comparison with Euclidean Embeddings -- 3.4. Cohort Specific Embeddings -- 4. Discussion and Conclusion -- 5. Acknowledgments -- References -- The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data -- 1. Introduction -- 2. Background -- 2.1. Multitask nets -- 3. Methods -- 3.1. Dataset Construction and Design -- 3.2. Experimental Design -- 4. Experiments and Results -- 4.1. When Does Multitask Learning Improve Performance? -- 4.2. Relationship Between Performance and Number of Tasks -- 4.3. Comparison with Logistic Regression Baseline -- 4.4. Interaction between Phenotype Prevalence and Complexity -- 5. Limitations -- 6. Conclusion -- Acknowledgments -- References -- ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites -- 1. Introduction -- 1.1. Integrate evidence from multiple clinical sites -- 1.2. Distributed Computing -- 2. Material and Method -- 2.1. Clinical Cohort and Motivating Problem -- 2.2. Algorithm -- 2.3. Simulation Design -- 3. Results -- 3.1. Simulation Results -- 3.2. Fetal Loss Prediction via ODAL -- 4. Discussion -- References.
PVC Detection Using a Convolutional Autoencoder and Random Forest Classifier -- 1. Introduction -- 2. Methods -- 2.1. Data Set and Implementation -- 2.2. Proposed PVC Detection Method -- 2.2.1. Feature Extraction -- 2.2.2. Classification -- 3. Results -- 3.1. Full Database Evaluation -- 3.2. Timing Disturbance Evaluation -- 3.3. Cross-Patient Training Evaluation -- 3.4. Estimated Parameters and Convergence -- 4. Discussion -- References -- Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications -- 1. Introduction -- 2. Related Work -- 3. Confounder Filtering (CF) Method -- 3.1. Overview -- 3.2. Method -- 3.3. Availability -- 4. Experiments -- 4.1. lung adenocarcinoma prediction -- 4.1.1. Data -- 4.1.2. Results -- 4.2. Segmentation on right ventricle(RV) of Heart -- 4.2.1. Data -- 4.2.2. Results -- 4.3. Students' confusion status prediction -- 4.3.1. Data -- 4.3.2. Results -- 4.4. Brain tumor prediction -- 4.4.1. Data -- 4.4.2. Results -- 4.5. Analyses of the method behaviors -- 5. Conclusion -- 6. Acknowledgement -- References -- DeepDom: Predicting protein domain boundary from sequence alone using stacked bidirectional LSTM -- 1. Introduction -- 2. METHODS -- 2.1 Data Set Preparation -- 2.2 Input Encoding -- 2.3 Model Architecture -- 2.4 Evaluation criteria -- 3. RESULTS AND DISCUSSION -- 3.1 Parameter configuration experiments on test data -- 3.2 Comparison with Other Domain Boundary Predictors -- 3.2.1 Free modeling targets from CASP 9 -- 3.2.2 Multi-domain targets from CASP 9 -- 3.2.3 Discontinuous domain target from CASP 8 -- 4. CONCLUSION -- 5. ACKNOWLEDGEMENTS -- REFERENCES -- Res2s2aM: Deep residual network-based model for identifying functional noncoding SNPs in trait-associated regions -- 1. Introduction -- 2. Background theory. 3. Dataset for training and testing -- 3.1. Source databases -- 3.2. Dataset generation -- 4. Methods -- 4.1. ResNet architecture in our model -- 4.2. Tandem inputs of forward- and reverse-strand sequences -- 4.3. Biallelic high-level network structure -- 4.4. Incorporating HaploReg SNP annotation features -- 4.5. Training of models -- 5. Results -- 6. Conclusions and discussion -- Acknowledgements -- References -- DNA Steganalysis Using Deep Recurrent Neural Networks -- 1. Introduction -- 2. Background -- 2.1. Notations -- 2.2. Hiding Messages -- 2.3. Determination of Message-Hiding Regions -- 3. Methods -- 3.1. Proposed DNA Steganalysis Principle -- 3.2. Proposed Steganalysis RNN Model -- 4. Results -- 4.1. Dataset -- 4.2. Input Representation -- 4.3. Model Training -- 4.4. Evaluation Procedure -- 4.5. Performance Comparison -- 5. Discussion -- Acknowledgments -- References -- Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature -- 1. Introduction -- 2. Related Work -- 3. Methods -- 3.1. Toponym Detection -- 3.1.1. Recurrent Neural Networks -- 3.1.2. LSTM -- 3.1.3. Other Gated RNN Architectures -- 3.1.4. Hyperparameter search and optimization -- 3.2. Toponym Disambiguation -- 3.2.1. Building Geonames Index -- 3.2.2. Searching Geonames Index -- 4. Results and Discussion -- 4.1. Toponym Disambiguation -- 4.2. Toponym Resolution -- 5. Limitations and Future Work -- 6. Conclusion -- Acknowledgments -- Funding -- References -- Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning -- 1. Introduction -- 2. Related Work -- 3. Method -- 3.1. Model Framework -- 3.2. Deep Reinforcement Learning for Organizing Actions -- 3.3. Preprocessing and Name Entity Recognition with UMLS -- 3.4. Bidirectional LSTM for Relation Classification. 3.5. Algorithm -- 3.6. Implementation Specification -- 4. Experiments -- 4.1. Data -- 4.2. Evaluation -- 4.3. Results -- 4.3.1. Improved Reliability -- 4.3.2. Robustness in Real-world Situations -- 4.3.3. Number of Articles Read -- 5. Conclusions and Future Work -- 6. Acknowledgement -- References -- Estimating classification accuracy in positive-unlabeled learning: characterization and correction strategies -- 1. Introduction -- 2. Methods -- 2.1. Performance measures: definitions and estimation -- 2.2. Positive-unlabeled setting -- 2.3. Performance measure correction -- 3. Experiments and Results -- 3.1. A case study -- 3.2. Data sets -- 3.3. Experimental protocols -- 3.4. Results -- 4. Conclusions -- Acknowledgements -- References -- PLATYPUS: A Multiple-View Learning Predictive Framework for Cancer Drug Sensitivity Prediction -- 1. Introduction -- 2. System and methods -- 2.1. Data -- 2.2. Single views and co-training -- 2.3. Maximizing agreement across views through label assignment -- 3. Results -- 3.1. Preliminary experiments to optimize PLATYPUS performance -- 3.2. Predicting drug sensitivity in cell lines -- 3.3. Key features from PLATYPUS models -- 4. Conclusions -- Acknowledgments -- References -- Computational KIR copy number discovery reveals interaction between inhibitory receptor burden and survival -- 1. Introduction -- 2. Materials and Methods -- 2.1 Data collection -- 2.2 K-mer selection -- 2.3 NGS pipeline and k-mer extraction -- 2.4 Data cleaning -- 2.5 Normalization of k-mer frequencies -- 2.6 Copy number segregation and cutoff selection -- 2.7 Validation of copy number -- 2.8 Survival analysis -- 2.9 Additional immune analysis -- 3. Results and Discussions -- 3.1 Establishing unique k-mers -- 3.2 Varying coverage of KIR region by exome capture kit -- 3.3 Inference of KIR copy number -- 3.4 Population variation of the KIR region. 3.5 KIR inhibitory gene burden correlates with survival in cervical and uterine cancer -- 5. Conclusions -- 6. Acknowledgements -- 7. Supplementary Material -- References -- Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier -- 1. Introduction -- 2. Data -- 2.1. Preprocessing -- 3. Deep Cancer Classifier -- 3.1. Training & -- testing -- 3.2. Parameter tuning -- 3.3. Feature importance -- 4. Results and Discussion -- 4.1. Model selection -- 4.2. Classifier performance -- 4.3. Comparison with other methods -- 4.4. Feature importance -- 5. Conclusion -- References -- Implementing and Evaluating A Gaussian Mixture Framework for Identifying Gene Function from TnSeq Data -- 1. Introduction -- 1.1. TnSeq Motivation and Background -- 1.2. Motivation and New Methods -- 2. Methods -- 2.1. TnSeq Experimental Data -- 2.2. Mixture framework -- 2.3. Classification methods -- 2.3.1. Novel method - EM -- 2.3.2. Current method - t-statistic -- 2.3.3. Bayesian hierarchical model -- 2.3.4. Data partitioning for the Bayesian model -- 2.4. Simulation -- 2.5. Real data -- 3. Results -- 3.1.1. Classification rate -- 3.1.2. False positive rate -- 3.1.3. Positive classification rate -- 3.1.4. Cross entropy -- 3.2. Simulation Results -- 3.3. Comparisons on real data -- 3.4. Software -- 4. Discussion -- References -- SNPs2ChIP: Latent Factors of ChIP-seq to infer functions of non-coding SNPs -- 1. Introduction -- 2. Results -- 2.1. SNPs2ChIP analysis framework overview -- 2.2. Batch normalization of heterogeneous epigenetic features -- 2.3. Latent factor discovery and their biological characterization -- 2.4. SNPs2ChIP identifies relevant functions of the non-coding genome -- 2.4.1. Genome-wide SNPs coverage of the reference datasets -- 2.4.2. Non-coding GWAS SNPs of systemic lupus erythematosus -- 2.4.3. ChIP-seq peaks for vitamin D receptors. 2.5. Robustness Analysis in the latent factor identification. |
Altri titoli varianti |
Biocomputing 2019
Biocomputing 2019:Proceedings of the Pacific Symposium:Pacific Symposium on Biocomputing 2019 |
Record Nr. | UNINA-9910349464803321 |
Altman Russ B | ||
World Scientific Publishing Co, 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Biocomputing 2021 - Proceedings Of The Pacific Symposium |
Autore | Altman Russ B |
Pubbl/distr/stampa | World Scientific Publishing Co, 2020 |
Descrizione fisica | 1 online resource (372 pages) |
Altri autori (Persone) |
DunkerA. Keith <1943-> (Alan Keith)
HunterLawrence <1961-> RitchieMarylyn D MurrayTiffany A KleinTeri E |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN | 981-12-3270-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Contents -- Preface -- ACHIEVING TRUSTWORTHY BIOMEDICAL DATA -- Session Introduction: Achieving Trustworthy Biomedical Data Solutions -- 1. Introduction -- 2. Preserving Privacy and Explaining Decisions of Artificial Intelligence -- 3. Sharing Genomic and Health Records -- 4. Deploying Digital Health Solutions -- 5. Crowdsourcing Healthcare -- 6. Considering the Bioethics -- 7. Anticipating the Future -- References -- Selection of Trustworthy Crowd Workers for Telemedical Diagnosis of Pediatric Autism Spectrum Disorder -- 1. Introduction -- 2. Methods -- 2.1. Clinically representative videos -- 2.2. Crowdsourcing task for Microworkers -- 2.3. Classifier to evaluate performance -- 2.4. Metrics evaluated -- 2.5. Prediction of crowd worker performance from metrics -- 3. Results -- 3.1. Correlation between metrics and probability of the correct class -- 3.2. Regression prediction of the mean probability of the correct class -- 4. Discussion and Future Work -- 5. Conclusion -- 6. Acknowledgments -- References -- Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data -- 1. Introduction -- 2. Related Work -- 3. Methods -- 3.1. Membership inference attack (MIA) -- 3.2. Di erential privacy (DP) -- 4. Experimental Setup -- 4.1. Dataset -- 4.2. Implementation of target models -- 4.3. Implementation of DP -- 4.4. Implementation of MIA -- 4.5. Evaluation metrics -- 5. Results -- 5.1. Vulnerability of target model against MIA without DP protection -- 5.2. Impact of privacy budget on the target model accuracy -- 5.3. E ectiveness of DP against MIA -- 5.4. E ect of model sparsity -- 6. Conclusion -- References -- Making Compassionate Use More Useful: Using Real-World Data, Real-World Evidence and Digital Twins to Supplement or Supplant Randomized Controlled Trials -- 1. Introduction.
1.1 Compassionate use -- 1.2 Compassionate use during the pandemic -- 1.3 What is an RCT? -- 1.3 EA data and NDAs -- 2. Real-World Information -- 2.1 Real-world data in trials -- 2.2 Real-world data and real-world evidence -- 2.2 Real-world limitations -- 3.0 Making RWD Work -- 3.1 Digital twins -- 4.0 Conclusions -- References -- ADVANCED METHODS FOR BIG DATA ANALYTICS IN WOMEN'S HEALTH -- Session Introduction: Advanced Methods for Big Data Analytics in Women's Health -- 1. Introduction -- 2. Session Summary -- 2.1. Full-length papers -- 3. Discussion -- References -- Intimate Partner Violence and Injury Prediction from Radiology Reports -- 1. Introduction -- 2. Related Work -- 2.1. Intimate partner violence -- 2.2. Clinical prediction -- 2.3. Natural language processing -- 3. Dataset -- 3.1. IPV patient selection -- 3.2. Control group selection -- 3.3. Injury labels -- 3.4. Data cleaning -- 3.5. Demographic data -- 4. Methodology -- 4.1. Experiment setup -- 4.2. Models -- 4.3. Evaluation -- 4.3.1. Prediction and predictive features -- 4.3.2. Error analysis -- 4.3.3. Report-program date gap -- 5. Results -- 5.1. IPV and injury prediction and predictive features -- 5.2. Error analysis -- 5.3. Report-program date gap -- 6. Discussion and conclusion -- References -- Not All C-sections Are the Same: Investigating Emergency vs. Elective C-section deliveries as an Adverse Pregnancy Outcome -- 1. Background and Significance -- 2. Methods -- 2.1. Dataset characteristics -- 2.2. Identification of delivery outcomes -- 2.2.1. Cesarean section deliveries -- 2.2.2. Preterm birth, stillbirth, and multiple birth deliveries -- 2.3. Integration of data from encounter records -- 2.4. Generalized regression models -- 3. Results -- 3.1. Utilization of cesarean section codes -- 3.2. Admission types recorded in encounter records. 3.3. Age distribution by delivery admit type -- 3.4. Number of deliveries by weekday and admit type -- 4. Generalized regression model -- 4.1. Surgical Incision Type for C-section and Effect on Emergency Admission -- 5. Discussion -- References -- Co-occurrence Patterns of Intimate Partner Violence -- 1. Introduction -- 2. Materials and Methods -- 2.1. Description of Data and Pre-Processing -- 2.2. Co-Occurrence of Violence Types -- 2.3. Co-Occurrence Network of Individual Violence Items -- 2.4. Radial Visualization -- 2.5. Clustering of Survivors and Identification of Subgroups -- 2.6. Health Problems and Trauma Symptoms -- 3. Results -- 4. Discussion -- 5. Acknowledgments -- References -- BIOCOMPUTING AND AI FOR INFECTIOUS DISEASE MODELLING AND THERAPEUTICS -- Session Introduction: AI for Infectious Disease Modelling and Therapeutics -- 1. Background -- 2. Introduction -- 3. Social Media and COVID-19 -- 4. Biomedical literature and COVID-19 plus neglected tropical diseases -- 5. Genomics and HCV -- 6. Protein intrinsically disordered regions and SARS-CoV-2 -- 7. Protein-protein interactions and SARS-CoV-2 -- References -- Characterization of Anonymous Physician Perspectives on COVID-19 Using Social Media Data -- 1. Introduction -- 2. Methods -- 2.1. Data Collection -- 2.2. N-gram Frequency Measures -- 2.3. Sentiment Analysis -- 3. Results -- 3.1. Frequency of terms and n-grams -- 3.2. Sentiment analysis -- 3.3. Sentiments of tweets containing specific terms -- 4. Discussion and Conclusion -- 5. Acknowledgments -- References -- Semantic Changepoint Detection for Finding Potentially Novel Research Publications -- 1. Introduction -- 2. Methods -- 2.1. Data collection and general procedures -- 2.2. Title and abstract entropies -- 2.3. Bayesian changepoint analysis -- 2.4. Differential word clouds -- 2.5. Title and abstract embeddings. 2.6. Semantic novelty -- 2.6.1. Strategy T1: Novel paper detection based on semantic distance -- 2.6.2. Strategy T2: Detection of novel papers that may constitute a trend -- 2.6.3. Strategy Y1: Detection of a group of novel papers based on their mean vector -- 2.6.4. Strategy Y2: Proportion of novel papers -- 3. Results and Discussion -- 4. Conclusions -- 5. Supplementary Information -- 6. Acknowledgements -- References -- TreeFix-TP: Phylogenetic Error-Correction for Infectious Disease Transmission Network Inference -- 1. Background -- 2. Methods -- 2.1. Minimizing inter-host transmissions -- 2.2. Description of TreeFix-TP -- 2.3. Evaluation using simulated data sets -- 2.3.1. Data set generation -- 2.3.2. Evaluating reconstruction accuracy -- 3. Results -- 3.1. Phylogenetic error correction results -- 3.2. Source recovery in HCV outbreaks -- 3.3. Running time and scalability -- 4. Discussion and Conclusions -- Acknowledgments -- Authors' Contributions -- Supplementary Material -- References -- SARS-CoV-2 Drug Discovery based on Intrinsically Disordered Regions -- 1. Introduction -- 2. Methods -- 2.1. Molecular docking -- 2.1.1. Data collection -- 2.1.2. Data preprocessing -- 2.1.3. Target file generation -- 2.1.4. Flexible docking -- 2.1.5. Ensemble docking -- 2.2. Statistical model -- 2.2.1. Chemprop -- 2.2.2. Data and training -- 3. Results -- 3.1. Interaction modelling -- 3.2. Activity prediction -- 4. Conclusion -- 5. Acknowledgements -- References -- Feasibility of the Vaccine Development for SARS-CoV-2 and Other Viruses Using the Shell Disorder Analysis -- 1. Introduction -- 1.1. SARS-COV-2 Vaccine -- 1.2. Shell disorder analysis of HIV and other viruses -- 1.3. Spinoff projects including coronaviruses: Shell disorder and modes of transmission -- 1.4. Yet another spinoff: Correlations between the inner shell disorder and virulence. 2. Results -- 2.1. Clustering of CoV based mainly on NPID -- 2.2 Outer shell disorder is an indicator for the presence or absence of effective vaccines -- 2.3. A disordered outer shell provides an immune evasion tactic: Viral shapeshifting -- 2.4. SARS-CoV-2: Exceptionally hard shell (low MPID) associated with burrowing animals and buried feces -- 2.5. Behavior of the animal hosts matters in the evolutions of the viruses: EIAV vs. HIV -- 2.6. Feasibility of developing attenuated vaccine strains for SARS-CoV-2 -- 3. Discussion -- 3.1. Links between respiratory transmission, N (Inner shell) disorder, and virulence: Viral load in body fluids vs. vital organs -- 3.2. Greater disorder in the inner shell proteins provide means for the more efficient replication of viral particles -- 3.3 Two modes of immune evasion: "Trojan Horse" (inner shell disorder) and "viral shapeshifting" (outer shell disorder) -- 3.4. FIV, HIV-1 and HIV-2: Similarities and differences -- 3.5. FIV vaccine enigma: Questionable efficacy -- 4. Conclusions -- 4.1. Development of the SARS-CoV-2 vaccine is feasible and vaccine strains can be found in nature -- 5. Materials and Methods -- References -- Protein Sequence Models for Prediction and Comparative Analysis of the SARS-CoV-2−Human Interactome -- 1. Introduction -- 2. Methods -- 2.1. Generalized Additive Models with interactions (GA2M) -- 3. Gold Standard Interaction Datasets -- 3.1. Dealing with the lack of negative examples -- 3.2. Features -- 4. Experiments -- 4.1. TAPE: Transformer based model for protein sequences -- 5. Results -- 5.1. Prediction performance and validation of predicted interactions -- 5.2. Enrichment analysis of predicted human binding partners -- 6. Discussion -- 6.1. Visualizing the virus-human interactions -- 6.2. Highly ranked sequence features -- 6.3. Structural analysis -- 7. Prior Work -- 8. Conclusion. 9. Acknowledgements. |
Altri titoli varianti | Biocomputing 2021 |
Record Nr. | UNINA-9910433229003321 |
Altman Russ B | ||
World Scientific Publishing Co, 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Pacific Symposium on Biocomputing 2015 : Kohala Coast, Hawaii, USA, 4-8 January 2015 / / edited by Russ B. Altman and five others |
Autore | Russ B Altman |
Pubbl/distr/stampa | World Scientific Publishing Co, 2014 |
Descrizione fisica | 1 online resource (viii, 505 pages) : illustrations |
Disciplina | 570.151 |
Soggetto topico |
Biology - Computer simulation - Congresses
Biology - Mathematical models - Congresses Molecular biology - Mathematical models - Congresses |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN | 981-4644-73-0 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910141778503321 |
Russ B Altman | ||
World Scientific Publishing Co, 2014 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Pacific Symposium on Biocomputing 2016 : Kohala Coast, Hawaii, USA, 4-8 January 2016 / / edited by Russ B. Altman and five others |
Autore | Russ B Altman |
Pubbl/distr/stampa | World Scientific Publishing Co, 2015 |
Descrizione fisica | 1 online resource (592 pages) : illustrations |
Disciplina | 570.113 |
Soggetto topico |
Biology - Computer simulation - Congresses
Biology - Mathematical models - Congresses Molecular biology - Computer simulation - Congresses |
Soggetto non controllato |
Protein Interactions
Metabolomics Biocomputing Computational Genetics Ontology Computational Proteomics Bioinformatics |
ISBN | 981-4749-41-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910137229403321 |
Russ B Altman | ||
World Scientific Publishing Co, 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|