Nantilus
Computational Intelligence Methods for Bioinformatics and Biostatistics : 8th International Meeting, CIBB 2011, Gargnano del Garda, Italy, June 30 July 2, 2011, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 8th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2011, held in Gargnano del Garda, Italy, in June/July 2011. The 19 papers, presented together with 2 keynote speeches, were...
Enregistré dans:
| Auteurs principaux : | , , , |
|---|---|
| Format : | Livre |
| Langue : | anglais |
| Titre complet : | Computational Intelligence Methods for Bioinformatics and Biostatistics : 8th International Meeting, CIBB 2011, Gargnano del Garda, Italy, June 30 July 2, 2011, Revised Selected Papers / edited by Elia Biganzoli, Alfredo Vellido, Federico Ambrogi, Roberto Tagliaferri. |
| Publié : |
Berlin, Heidelberg :
Springer Berlin Heidelberg
, 2012 Cham : Springer Nature |
| Collection : | Lecture notes in bioinformatics (Online) |
| Accès en ligne : |
Accès Nantes Université
Accès direct soit depuis les campus via le réseau ou le wifi eduroam soit à distance avec un compte @etu.univ-nantes.fr ou @univ-nantes.fr |
| Sujets : | |
| Documents associés : | Autre format:
Computational Intelligence Methods for Bioinformatics and Biostatistics Autre format: Computational Intelligence Methods for Bioinformatics and Biostatistics |
| LEADER | 05443clm a2200685 4500 | ||
|---|---|---|---|
| 001 | PPN16832914X | ||
| 003 | http://www.sudoc.fr/16832914X | ||
| 005 | 20241001155200.0 | ||
| 010 | |a 978-3-642-35686-5 | ||
| 017 | 7 | 0 | |a 10.1007/978-3-642-35686-5 |2 DOI |
| 035 | |a (OCoLC)829433952 | ||
| 035 | |a Springer978-3-642-35686-5 | ||
| 035 | |a Springer-11645-978-3-642-35686-5 | ||
| 100 | |a 20130325d2012 u u0frey0103 ba | ||
| 101 | 0 | |a eng |2 639-2 | |
| 102 | |a DE | ||
| 135 | |a dr||||||||||| | ||
| 181 | |6 z01 |c txt |2 rdacontent | ||
| 181 | 1 | |6 z01 |a i# |b xxxe## | |
| 182 | |6 z01 |c c |2 rdamedia | ||
| 182 | 1 | |6 z01 |a b | |
| 183 | |6 z01 |a ceb |2 RDAfrCarrier | ||
| 200 | 1 | |a Computational Intelligence Methods for Bioinformatics and Biostatistics |e 8th International Meeting, CIBB 2011, Gargnano del Garda, Italy, June 30 July 2, 2011, Revised Selected Papers |f edited by Elia Biganzoli, Alfredo Vellido, Federico Ambrogi, Roberto Tagliaferri. | |
| 214 | 0 | |a Berlin, Heidelberg |c Springer Berlin Heidelberg | |
| 214 | 2 | |a Cham |c Springer Nature |d 2012 | |
| 225 | 0 | |a Lecture Notes in Bioinformatics |x 2366-6331 |v 7548 | |
| 330 | |a This book constitutes the thoroughly refereed post-proceedings of the 8th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2011, held in Gargnano del Garda, Italy, in June/July 2011. The 19 papers, presented together with 2 keynote speeches, were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on statistical learning, genomics, computational intelligence for health at the edge, proteomics, intelligent clinical decision support systems (i-CDSS), bioinformatics, and data clustering. | ||
| 359 | 1 | |a Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic -- Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Genomic Data: Two Examples from Rare Genetic Diseases and Infectious Diseases -- Bayesian Models for the Multi-sample Time-Course Microarray Experiments -- A Machine Learning Pipeline for Discriminant Pathways Identification -- Discovering Hidden Pathways in Bioinformatics -- Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models -- A Bioinformatics Procedure to Identify and Annotate Somatic Mutations in Whole-Exome Sequencing Data -- Feature Selection for the Prediction and Visualization of Brain Tumor Types Using Proton Magnetic Resonance Spectroscopy Data -- On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statins -- Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biomedical Knowledge Discovery -- Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins -- Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree -- DEEN: A Simple and Fast Algorithm for Network Community Detection -- Self-similarity in Physiological Time Series: New Perspectives from the Temporal Spectrum of Scale Exponents -- Support Vector Machines for Survival Regression -- Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Prediction -- A Faster Algorithm for Motif Finding in Sequences from ChIP-Seq Data -- Case/Control Prediction from Illumina Methylation Microarray s b and Two-Color Channels in the Presence of Batch Effects -- Supporting the Design, Communication and Management of Bioinformatic Protocols through the Leaf Tool -- Genomic Annotation Prediction Based on Integrated Information -- Solving Biclustering with a GRASP-Like Metaheuristic: Two Case-Studies on Gene ExpressionAnalysis. | |
| 371 | 0 | |a L'accès complet à la ressource est réservé aux usagers des établissements qui en ont fait l'acquisition | |
| 410 | | | |0 191524395 |t Lecture notes in bioinformatics (Online) |x 2366-6331 | |
| 452 | | | |t Computational Intelligence Methods for Bioinformatics and Biostatistics |b Texte imprimé |y 9783642356858 | |
| 452 | | | |t Computational Intelligence Methods for Bioinformatics and Biostatistics |b Texte imprimé |y 9783642356872 | |
| 610 | 1 | |a Computer Science | |
| 610 | 2 | |a Artificial Intelligence (incl. Robotics) | |
| 610 | 2 | |a Computation by Abstract Devices | |
| 610 | 2 | |a Algorithm Analysis and Problem Complexity | |
| 610 | 2 | |a Pattern Recognition | |
| 610 | 2 | |a Database Management | |
| 610 | 2 | |a Bioinformatics | |
| 610 | 2 | |a Artificial Intelligence. | |
| 610 | 1 | |a Theory of Computation | |
| 610 | 2 | |a Automated Pattern Recognition | |
| 610 | 2 | |a Algorithms | |
| 615 | |a @Computer Science |n 11645 |2 Springer | ||
| 615 | |a Computer Science |n 11645 |2 Springer | ||
| 676 | |a 004.0151 |v 23 | ||
| 680 | |a QA75.5-76.95 | ||
| 700 | 1 | |a Biganzoli |b Elia | |
| 701 | 1 | |a Biganzoli |b Elia |4 651 | |
| 701 | 1 | |a Vellido |b Alfredo |4 651 | |
| 701 | 1 | |a Ambrogi |b Federico |4 651 | |
| 701 | 1 | |a Tagliaferri |b Roberto |4 651 | |
| 801 | 3 | |a FR |b Abes |c 20240611 |g AFNOR | |
| 801 | 1 | |a DE |b Springer |c 20240603 |g AACR2 | |
| 856 | 4 | |5 441099901:830856773 |u https://budistant.univ-nantes.fr/login?url=https://doi.org/10.1007/978-3-642-35686-5 | |
| 915 | |5 441099901:830856773 |b SPRING13-00708 | ||
| 930 | |5 441099901:830856773 |b 441099901 |j g | ||
| 991 | |5 441099901:830856773 |a Exemplaire créé en masse par ITEM le 30-09-2024 16:13 | ||
| 997 | |a NUM |b SPRING13-00708 |d NUMpivo |e EM |s d | ||
| 998 | |a 978538 | ||