Kooperativer Bibliotheksverbund

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Umfang: 1 online resource (471 pages)

ISBN: 981-327-982-6 , 981-327-981-8

Inhalt: The Pacific Symposium on Biocomputing (PSB) 2019 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2019 will be held on January 3 – 7, 2019 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference. PSB 2019 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's "hot topics." In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Anmerkung: 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. , English

Sprache: Englisch

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Umfang: 1 online resource (306)

Ausgabe: 1st ed.

ISBN: 3-8394-0199-2

Serie: Sozialtheorie

Inhalt: Ob Körperbewegung oder Tanzbewegung, ob Bewegung der Bilder, der Töne oder der Schrift, ob soziale oder politische Bewegung, der Begriff »Bewegung« wird in Ästhetik, Kultur- und Sozialwissenschaften häufig benutzt. Anders als in den Naturwissenschaften aber ist dem konzeptuellen Stellenwert des Bewegungsbegriffs in den Kultur- und Sozialwissenschaften bislang nur wenig Aufmerksamkeit geschenkt worden. Die interdisziplinäre Textsammlung verfolgt das Ziel, den Status quo des Begriffs in den Sozial- und Kulturwissenschaften zu reflektieren und sein theoretisches Potenzial zu bestimmen. Sie geht von der Annahme aus, dass Bewegung nicht nur eine »physikalische Tatsache« und damit etwas quasi Natürliches ist, sondern ein soziales und kulturelles Konzept, das auf verschiedene Weise naturalisiert und essenzialisiert worden ist. Der Band präsentiert verschiedene Gebrauchsweisen des Begriffs und ermöglicht damit ein weiteres konzeptuelles Nachdenken über Bewegung als einen Begriff, dessen Rolle im »Tanz der Disziplinen« neu zu entfalten ist.

Inhalt: Besprochen in: IFIS, 4 (2005), Braun-Laufer

Anmerkung: Frontmatter 1 Inhalt 5 Bewegung und Moderne: Zur Einführung 7 Ordnung und Erinnerung. Menschliche Bewegung in der Perspektive der historischen Anthropologie 23 Bewegung und Gesellschaft. Zur "Verkörperung" des Sozialen und zur Formung des Selbst in Sport und populärer Kultur 43 Handlung, Funktion, Dialog, Symbol. Menschliche Bewegung aus entwicklungspädagogischer Sicht 79 Bewegung - eine spezifische Form nicht-propositionalen Wissens 109 Bewegung denken. Ein soziologischer Entwurf 131 Die Gleichförmigkeit und die Bewegtheit des Subjekts: Moderne Subjektivität im Konflikt von bürgerlicher und avantgardistischer Codierung 155 Kohärentes Bewegen. Grundlagen eines wissenschaftlichen Denkens durch das Bewegen 185 Bewegung. Die Wege Heideggers 201 Was bewegt sich in sozialen Bewegungen? Bewegungsmetaphorik und politisches Handeln 217 ,Sich bewegen, um die Verhältnisse zu verändern.' Räumliche, subjektbezogene und politische Dimensionen des Bewegungsbegriffs in der feministischen Theorie und Praxis 239 Bewegung zeigen oder Bewegung schreiben? Der Film als symbolische Form der Moderne 265 Bewegung als Konzept der Zeit: Figuren der Zeitmessung 283 Hinweise zu den Autorinnen und Autoren 303 Backmatter 306 , German.

Weitere Ausg.: ISBN 3-89942-199-X

Sprache: Deutsch

Fachgebiete: Soziologie

Schlagwort(e): Electronic books.

DOI: 10.14361/9783839401996

URL: lizenzpflichtig

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UID:

Umfang: 1 online resource (X, 348 p.)

ISBN: 3-11-072960-1

Serie: Sprache und Wissen (SuW) ; 49

Inhalt: In spite of extensive research in the field of cultural studies, the topic of fear has not yet been exhausted, especially considering that not even the semantics of its linguistic devices or the diversity of its linguistic constructions have been satisfactorily explained. This study looks to the present day to examine which media generate fear by which means and manage to assert themselves as an acceptable perspective on social reality.

Inhalt: Trotz einer Vielzahl kulturwissenschaftlicher Forschung ist Angst kein ausdiskutiertes Thema, insofern als nicht einmal die Semantiken der sprachlichen Ausdrucksmittel oder die Vielfalt der Konstruktionsformen genügend geklärt sind. Mit Blick auf die Gegenwart gilt es zu eruieren, welche Medien Ängste mit welchen Mitteln erzeugen und als angemessene Perspektive auf die soziale Wirklichkeit durchsetzen. Diesen Fragestellungen widmet sich der Band.

Anmerkung: Description based upon print version of record. , Frontmatter -- , Open-Access-Transformation in der Linguistik -- , Vorwort und Danksagung -- , Inhalt -- , Angstkonstruktion: Interdisziplinäre Annäherungen an eine Zeitdiagnose und ein Versuch ihrer linguistischen und literaturwissenschaftlichen Präzisierung -- , Philosophische Reflexion zu den Spielarten kollektiver Furcht -- , Jean Delumeau (1923-2020) und die Entdeckung des "pays de la peur" -- , Verbotene Räume -- , A Matter of Perspective -- , "Sie werden nun ziemlich furchtsam sein". Zukunftsangst in der mittelalterlichisländischen Sagaliteratur -- , Die Darstellung und Funktion von Angst im Märchen Schneewittchen -- , Angst in der Ratgeberliteratur -- , Angstkonstruktionen zwischen "sinnvoller Vorsicht und sinnloser Panik" -- , Das böse Wort mit C -- , Die Stimmung kippt (nicht von allein) -- , Fear as an Affective Trait -- , Autorenverzeichnis -- , Index , In German.

Weitere Ausg.: ISBN 3-11-073126-6

Sprache: Deutsch

Schlagwort(e): Electronic books. ; Electronic books.

DOI: 10.1515/9783110729603

URL: De Gruyter

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URL: EBSCOhost

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Umfang: 1 online resource (649 pages)

ISBN: 981-323-553-5

Inhalt: The Pacific Symposium on Biocomputing (PSB) 2018 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2018 will be held on January 3 – 7, 2018 in Kohala Coast, Hawaii. PSB 2018 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's "hot topics." In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Anmerkung: English

Weitere Ausg.: ISBN 981-323-552-7

Sprache: Englisch

Schlagwort(e): Electronic books ; Electronic books ; Electronic books.

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Umfang: 1 online resource (372 pages)

ISBN: 981-12-3270-9

Inhalt: The Pacific Symposium on Biocomputing (PSB) 2021 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2021 will be held on a virtual platform at http://psb.stanford.edu/ on January 5–7, 2021. Tutorials and workshops will be offered prior to the start of the conference. PSB 2021 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's "hot topics." In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Anmerkung: 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. , English

Weitere Ausg.: ISBN 981-12-3269-5

Sprache: Englisch

Schlagwort(e): Electronic books.

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Umfang: 1 online resource (480 p.)

ISBN: 2-7605-2165-6 , 1-4356-8513-X

Anmerkung: Textes presentes lors d'un colloque organise par le Centre de recherche sur l'innovation sociale et tenu en nov. 2004 à l'Universite du Quebec à Montreal. , Avant-Propos; Table des matières; Introduction; Partie 1_L'innovation sociale comme facteur de changement social; Chapitre 1_L'innovation sociale; Chapitre 2_L'innovation dans le développement économique et le développement social; Chapitre 3_L'innovation sociale au coeur des débats publics et scientifiques; Chapitre 4_Éléments pour l'analyse du changement social démocratique; Chapitre 5_L'innovation sociale en économie sociale; Chapitre 6_On ne peut pas institutionnaliser l'innovation; Partie 2_Dynamiques sectorielles croisées , Chapitre 7_Gouvernance territoriale, puissance publique et société civileChapitre 8_Les collectivités apprenantes; Chapitre 9_Flexible, branché, mais dans un cul-de-sac; Chapitre 10_Formes sociales et formes marchandes; Chapitre 11_A-t-on appris et innové?; Partie 3_Champs d'expérimentation; Chapitre 12_L'argent ou l'Être humain?; Chapitre 13_Le soutien au local au Royaume-Uni; Chapitre 14_Innovation et changement de société; Chapitre 15_Liens sociaux et innovation institutionnelle; Chapitre 16_Innovation sociale et société innovante; Partie 4_Un programme de recherche , Chapitre 17_Axe 1 - Travail et emploiChapitre 18_Axe 2 - Conditions de vie; Chapitre 19_Axe 3 - Développement et territoire; Partie 5_L'innovation sociale; Chapitre 20_La dialectique de l'innovation sociale et de l'institutionnalisation; Chapitre 21_Innovation et changement social; Chapitre 22_L'innovation sociale et ses acteurs; Bibliographie générale; Liste des auteurs , French

Weitere Ausg.: ISBN 2-7605-1374-2

Sprache: Französisch

Schlagwort(e): Electronic books. ; Electronic books.