標(biāo)題: Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 8th International Me Elia Biganzoli,Alfredo Vellido,Roberto Taglia [打印本頁] 作者: 一再 時(shí)間: 2025-3-21 20:07
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics影響因子(影響力)
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics影響因子(影響力)學(xué)科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics網(wǎng)絡(luò)公開度
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics被引頻次
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics被引頻次學(xué)科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics年度引用
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics年度引用學(xué)科排名
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics讀者反饋
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics讀者反饋學(xué)科排名
作者: 行業(yè) 時(shí)間: 2025-3-21 22:59
A Bioinformatics Procedure to Identify and Annotate Somatic Mutations in Whole-Exome Sequencing Dataation and visualization of results. We analyzed whole exome sequencing data from 3 leukemic patients and 3 paired controls plus 1 colon cancer sample and paired control. The results were validated by Sanger sequencing.作者: Priapism 時(shí)間: 2025-3-22 04:18 作者: 反叛者 時(shí)間: 2025-3-22 07:30
Self-similarity in Physiological Time Series: New Perspectives from the Temporal Spectrum of Scale Elevels of cardiac sympatho/vagal balance. Results reveal the limits of the traditional “l(fā)umped-parameter” approach, and provide information on the role of autonomic outflows in determining cardiovascular self-similarity.作者: PSA-velocity 時(shí)間: 2025-3-22 10:28
Case/Control Prediction from Illumina Methylation Microarray’s , and Two-Color Channels in the Presethan . and ., interpreting that U’s low prediction impacts negatively the one of .. We also confirm that without proper batch effect cancellation, non-biological variance hides the biological signal, making impractical the prediction of case status.作者: ALT 時(shí)間: 2025-3-22 13:03
,Stochastik – eine Wissenschaft für sich,ation and visualization of results. We analyzed whole exome sequencing data from 3 leukemic patients and 3 paired controls plus 1 colon cancer sample and paired control. The results were validated by Sanger sequencing.作者: ALT 時(shí)間: 2025-3-22 18:50
Theorie der stochastischen Prozesse,ls are evaluated according to their accuracy, simplicity and medical interpretability. We also explore the influence of redundancy in the modelling process. Our results suggest that a moderate amount of redundant metabolites can actually enhance class-separability and therefore accuracy.作者: Malleable 時(shí)間: 2025-3-23 00:30 作者: OTHER 時(shí)間: 2025-3-23 05:20
https://doi.org/10.1007/978-3-0348-5802-1than . and ., interpreting that U’s low prediction impacts negatively the one of .. We also confirm that without proper batch effect cancellation, non-biological variance hides the biological signal, making impractical the prediction of case status.作者: 陶瓷 時(shí)間: 2025-3-23 06:23 作者: 調(diào)情 時(shí)間: 2025-3-23 12:31 作者: conifer 時(shí)間: 2025-3-23 17:21 作者: 向宇宙 時(shí)間: 2025-3-23 18:44
A Machine Learning Pipeline for Discriminant Pathways Identificationystems biology. In this work we propose a pipeline that couples a machine learning solution for molecular profiling with a recent network comparison method. The pipeline can identify changes occurring between specific sub-modules of networks built in a case-control biomarker study, discriminating ke作者: Dappled 時(shí)間: 2025-3-24 01:56 作者: 典型 時(shí)間: 2025-3-24 04:46 作者: Handedness 時(shí)間: 2025-3-24 07:20
A Bioinformatics Procedure to Identify and Annotate Somatic Mutations in Whole-Exome Sequencing Data problem to store, manage and analyze terabytes of sequencing data often generated from extremely different data-sources. Our project is mainly focused on the sequence analysis of human cancer genomes, in order to identify the genetic lesions underlying the development of tumors. However, the automa作者: Deject 時(shí)間: 2025-3-24 14:38 作者: habitat 時(shí)間: 2025-3-24 16:32 作者: 脆弱么 時(shí)間: 2025-3-24 22:04
Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Bitive data management and analysis support. Integration and comprehensive evaluation of available controlled data can highlight information patterns leading to unveil new biomedical knowledge. For this purpose, the University Politecnico di Milano, is developing a software framework to create and mai作者: 紅潤 時(shí)間: 2025-3-25 02:37
Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins Support Vector Machines (HM-SVM) have been shown to be among the best performing methods on this task. Furthermore, it has been noted that the performance of a predictor improves when its input takes advantage of the difference between observed and predicted residue solvent accessibility. In this p作者: Glucocorticoids 時(shí)間: 2025-3-25 06:58
Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Treee challenge of finding robust methods to analyze the complex data they generate. In this brief paper, we focus on the analysis of a specific type of proteins, the G protein-couple receptors, which are the target for over 15% of current drugs. We describe a kernel method of the manifold learning fami作者: 歡呼 時(shí)間: 2025-3-25 07:38 作者: Hemodialysis 時(shí)間: 2025-3-25 13:42
Self-similarity in Physiological Time Series: New Perspectives from the Temporal Spectrum of Scale Elly assessed by detrended fluctuation analysis (DFA) assuming that mono- or bi-fractal models generate the self-similar dynamics. Our group recently proposed a new DFA approach describing self-similarity as a continuous temporal spectrum of coefficients, thus not assuming that “l(fā)umped-parameter” fra作者: 露天歷史劇 時(shí)間: 2025-3-25 18:04
Support Vector Machines for Survival Regressionerspective. We define an appropriate weighted loss function which takes into account possibly censored observations, and we prove bounds on the estimation error and on the quantile property. We deduce that censoring is a limiting factor in the accuracy of solutions, though the overall rate of conver作者: 染色體 時(shí)間: 2025-3-25 22:33
Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Predictionsive bladder cancer progression prediction. The proposed methodology combines knowledge discovery in data using artificial intelligence and knowledge mining. These are used both in feature selection and classifier development. The approach is designed to avoid overfitting and overoptimistic results.作者: Accomplish 時(shí)間: 2025-3-26 02:57 作者: Folklore 時(shí)間: 2025-3-26 08:00
Case/Control Prediction from Illumina Methylation Microarray’s , and Two-Color Channels in the Prese analyse ., thus making . a . standard. Further, as . combines the two color channels . and . into the ratio ./(.?+?.), we also assume, maybe naively, that . conveys more biologically relevant information than a single color taken alone. As well, a fourth of the GEO studies do not report any analysi作者: Friction 時(shí)間: 2025-3-26 09:49
Supporting the Design, Communication and Management of Bioinformatic Protocols through the Leaf Toolitself a precious tool to replicate the analysis, this is in practice often hard to realize. In this paper we try to formalize the concept of protocol in bioinformatic data analysis and introduce the Leaf System, including a graph design language to define the main steps of the data analysis and a P作者: harrow 時(shí)間: 2025-3-26 12:58 作者: Keshan-disease 時(shí)間: 2025-3-26 19:35
Maria Overbeck-Larisch,Wolfgang Dolejskyr demonstrates that it is possible to model and trace over time the effect of a gene on the total spiking behavior of the SNN when the gene controls a parameter of a stochastic spiking neuron model used to build the SNN. Such CNGM can be potentially used to study neurodegenerative diseases or develop CNGM for cognitive robotics.作者: canvass 時(shí)間: 2025-3-26 23:50 作者: 青春期 時(shí)間: 2025-3-27 03:57 作者: upstart 時(shí)間: 2025-3-27 09:15
Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computatir demonstrates that it is possible to model and trace over time the effect of a gene on the total spiking behavior of the SNN when the gene controls a parameter of a stochastic spiking neuron model used to build the SNN. Such CNGM can be potentially used to study neurodegenerative diseases or develop CNGM for cognitive robotics.作者: optional 時(shí)間: 2025-3-27 10:40 作者: 徹底明白 時(shí)間: 2025-3-27 15:53
Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Predictionmining. These are used both in feature selection and classifier development. The approach is designed to avoid overfitting and overoptimistic results. To our knowledge, these are the first intelligent systems for prediction of bladder cancer progression, based on boosted C5 decision trees, and their accuracy of 100% is the best published by now.作者: 皺痕 時(shí)間: 2025-3-27 20:11
Conference proceedings 2012cs 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 in作者: CURT 時(shí)間: 2025-3-28 01:36
https://doi.org/10.1007/978-3-322-86275-4d with severe sepsis and multi-organ failure at the ICU of Vall d’Hebrón University Hospital (Barcelona, Spain). Outcome was predicted using statistic algebraic models and the Bayesian Networks that can naturally be derived from these models.作者: Corral 時(shí)間: 2025-3-28 02:34
https://doi.org/10.1007/978-3-322-93058-3ify clusters containing proteins with the same functional category, improving on ., a popular state-of-the-art method for functional protein complex detection. Moreover, application of ., to two popular benchmark networks results in the detection of accurate communities, substantiating the effectiveness of the proposed method in diverse domains.作者: fringe 時(shí)間: 2025-3-28 07:43
https://doi.org/10.1007/978-3-322-93058-3ed new challenges for the design of efficient algorithms able to produce results in reasonable time. In this work we present an updated version of our algorithm Weeder, in which time and space requirements are significantly reduced and, moreover, also the accuracy of the results is notably improved.作者: muffler 時(shí)間: 2025-3-28 13:24
On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statid with severe sepsis and multi-organ failure at the ICU of Vall d’Hebrón University Hospital (Barcelona, Spain). Outcome was predicted using statistic algebraic models and the Bayesian Networks that can naturally be derived from these models.作者: Incise 時(shí)間: 2025-3-28 16:22 作者: atopic-rhinitis 時(shí)間: 2025-3-28 19:36 作者: 憤慨點(diǎn)吧 時(shí)間: 2025-3-29 00:44
Conference proceedings 2012 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.作者: 有節(jié)制 時(shí)間: 2025-3-29 03:06 作者: aviator 時(shí)間: 2025-3-29 10:39
Norbert Henze,Kai Müller,Judith Schillingy groups of genes whose interactions are modified by an underlying condition. The proposal is independent from the classification algorithm used. Two applications on genomewide data are presented regarding children susceptibility to air pollution and early and late onset of Parkinson’s disease.作者: Diaphragm 時(shí)間: 2025-3-29 13:24
Norbert Henze,Kai Müller,Judith Schilling blind source separation to map the pathways of biomarkers driving independent, hidden processes that underpin the clusters. The method is applied to a protein expression data set measured in tissue from breast cancer patients (.=1,076).作者: 強(qiáng)行引入 時(shí)間: 2025-3-29 18:09
Wolfgang Hackenbroch,Anton Thalmaieraper, for first time, we combine these elements and we present ISPRED2, a new HM-SVM-based method that overpasses the state of the art performance (Q2=0.71 and correlation=0.43). ISPRED2 consists of a sets of Python scripts aimed at integrating the different third-party software to obtain the final prediction.作者: 我不重要 時(shí)間: 2025-3-29 19:56 作者: 不再流行 時(shí)間: 2025-3-30 02:00 作者: glomeruli 時(shí)間: 2025-3-30 05:18
https://doi.org/10.1007/978-3-658-33779-7ompromise between nonparametric and normality assumption based techniques. In addition, all evaluations are carried out using analytic expressions, hence, the entire procedure requires very small computational effort. The performance of the procedure is studied using simulated data.作者: exorbitant 時(shí)間: 2025-3-30 08:43 作者: 摘要記錄 時(shí)間: 2025-3-30 13:44 作者: 使無效 時(shí)間: 2025-3-30 16:37
Bayesian Models for the Multi-sample Time-Course Microarray Experimentsompromise between nonparametric and normality assumption based techniques. In addition, all evaluations are carried out using analytic expressions, hence, the entire procedure requires very small computational effort. The performance of the procedure is studied using simulated data.作者: extract 時(shí)間: 2025-3-30 23:52
Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models in terms of within-sample repeatability and between-lines reproducibility. Validation on publicly available NCI60 dataset showed similar patterns of variability, suggesting good reproducibility between experiments..Future research will explore the possibility to use this method to compare normalization methods as well as genomic platforms.作者: Substance 時(shí)間: 2025-3-31 01:39
Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biata in the GPDW. The comprehensive and mining of the reliable interaction data together with the other biomolecular information in the GPDW constitutes a powerful computational support for novel biomedical knowledge discoveries.作者: aviator 時(shí)間: 2025-3-31 05:58
Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Gen of datasets from Gene Therapy and Tubercolosis to highlight how integration between biostatistics and bioinformatics allows to gain information from the extremely large biogical databases produced with the new biotechnologies, such as Next Generation Sequencing (NGS) data.作者: Eclampsia 時(shí)間: 2025-3-31 10:34 作者: 犬儒主義者 時(shí)間: 2025-3-31 17:20 作者: forager 時(shí)間: 2025-3-31 19:51 作者: 過剩 時(shí)間: 2025-4-1 00:29 作者: –FER 時(shí)間: 2025-4-1 03:02 作者: echnic 時(shí)間: 2025-4-1 10:03 作者: 繁重 時(shí)間: 2025-4-1 13:22
Maria Overbeck-Larisch,Wolfgang Dolejskytwork (SNN) model at a higher level to model the dynamic interaction between genes and spiking patterns of activity under certain conditions. The paper demonstrates that it is possible to model and trace over time the effect of a gene on the total spiking behavior of the SNN when the gene controls a作者: defendant 時(shí)間: 2025-4-1 16:23 作者: 鞠躬 時(shí)間: 2025-4-1 21:57
https://doi.org/10.1007/978-3-658-33779-7 identify the nature of differential expression (e.g., gene is differentially expressed between the first and the second sample but is not differentially expressed between the second and the third) and subsequently we estimate gene expression temporal profiles. The proposed procedure deals successfu作者: Salivary-Gland 時(shí)間: 2025-4-2 02:16
Norbert Henze,Kai Müller,Judith Schillingystems biology. In this work we propose a pipeline that couples a machine learning solution for molecular profiling with a recent network comparison method. The pipeline can identify changes occurring between specific sub-modules of networks built in a case-control biomarker study, discriminating ke作者: BORE 時(shí)間: 2025-4-2 03:33 作者: Provenance 時(shí)間: 2025-4-2 09:35 作者: CARK 時(shí)間: 2025-4-2 13:50
,Stochastik – eine Wissenschaft für sich, problem to store, manage and analyze terabytes of sequencing data often generated from extremely different data-sources. Our project is mainly focused on the sequence analysis of human cancer genomes, in order to identify the genetic lesions underlying the development of tumors. However, the automa
