Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)最新文献

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Adenine: A HPC-Oriented Tool for Biological Data Exploration 腺嘌呤:一个面向高性能计算机的生物数据探索工具
Samuele Fiorini, Federico Tomasi, M. Squillario, A. Barla
{"title":"Adenine: A HPC-Oriented Tool for Biological Data Exploration","authors":"Samuele Fiorini, Federico Tomasi, M. Squillario, A. Barla","doi":"10.1007/978-3-030-14160-8_6","DOIUrl":"https://doi.org/10.1007/978-3-030-14160-8_6","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"23 1","pages":"51-59"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73458719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Experimental Evidences Suggest High Between-Vesicle Diversity of Artificial Vesicle Populations: Results, Models and Implications 实验证据表明人工囊泡种群具有高度囊泡间多样性:结果、模型和意义
P. Stano, R. Marangoni, F. Mavelli
{"title":"Experimental Evidences Suggest High Between-Vesicle Diversity of Artificial Vesicle Populations: Results, Models and Implications","authors":"P. Stano, R. Marangoni, F. Mavelli","doi":"10.1007/978-3-030-14160-8_17","DOIUrl":"https://doi.org/10.1007/978-3-030-14160-8_17","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"38 1","pages":"171-185"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79787463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Structural Features of a DPPG Liposome Layer Adsorbed on a Rough Surface 粗糙表面吸附DPPG脂质体层的结构特征
M. Raposo, A. A. Duarte, P. J. Gomes, P. Ribeiro, M. L. Moraes, R. Steitz
{"title":"Structural Features of a DPPG Liposome Layer Adsorbed on a Rough Surface","authors":"M. Raposo, A. A. Duarte, P. J. Gomes, P. Ribeiro, M. L. Moraes, R. Steitz","doi":"10.1007/978-3-030-14160-8_14","DOIUrl":"https://doi.org/10.1007/978-3-030-14160-8_14","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"54 1","pages":"138-144"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85625966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Cancer Mutational Signatures Identification with Sparse Dictionary Learning 基于稀疏字典学习的癌症突变特征识别
Veronica Tozzo, A. Barla
{"title":"Cancer Mutational Signatures Identification with Sparse Dictionary Learning","authors":"Veronica Tozzo, A. Barla","doi":"10.1007/978-3-030-14160-8_4","DOIUrl":"https://doi.org/10.1007/978-3-030-14160-8_4","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"98 1","pages":"32-41"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79477535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Quantitative and Qualitative Characterization of k-mer Based Alignment-Free Phylogeny Construction 基于k-mer的无比对系统发育构建的定量和定性研究
F. Utro, D. Platt, L. Parida
{"title":"A Quantitative and Qualitative Characterization of k-mer Based Alignment-Free Phylogeny Construction","authors":"F. Utro, D. Platt, L. Parida","doi":"10.1007/978-3-030-14160-8_3","DOIUrl":"https://doi.org/10.1007/978-3-030-14160-8_3","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"63 ","pages":"19-31"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91519497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
DeepScope: Nonintrusive Whole Slide Saliency Annotation and Prediction from Pathologists at the Microscope. DeepScope:来自显微镜下病理学家的非侵入式全切片 Saliency 注释和预测。
Andrew J Schaumberg, S Joseph Sirintrapun, Hikmat A Al-Ahmadie, Peter J Schüffler, Thomas J Fuchs
{"title":"DeepScope: Nonintrusive Whole Slide Saliency Annotation and Prediction from Pathologists at the Microscope.","authors":"Andrew J Schaumberg, S Joseph Sirintrapun, Hikmat A Al-Ahmadie, Peter J Schüffler, Thomas J Fuchs","doi":"10.1007/978-3-319-67834-4_4","DOIUrl":"10.1007/978-3-319-67834-4_4","url":null,"abstract":"<p><p>Modern digital pathology departments have grown to produce whole-slide image data at petabyte scale, an unprecedented treasure chest for medical machine learning tasks. Unfortunately, most digital slides are not annotated at the image level, hindering large-scale application of supervised learning. Manual labeling is prohibitive, requiring pathologists with decades of training and outstanding clinical service responsibilities. This problem is further aggravated by the United States Food and Drug Administration's ruling that primary diagnosis must come from a glass slide rather than a digital image. We present the first end-to-end framework to overcome this problem, gathering annotations in a nonintrusive manner during a pathologist's routine clinical work: (i) microscope-specific 3D-printed commodity camera mounts are used to video record the glass-slide-based clinical diagnosis process; (ii) after routine scanning of the whole slide, the video frames are registered to the digital slide; (iii) motion and observation time are estimated to generate a spatial and temporal saliency map of the whole slide. Demonstrating the utility of these annotations, we train a convolutional neural network that detects diagnosis-relevant salient regions, then report accuracy of 85.15% in bladder and 91.40% in prostate, with 75.00% accuracy when training on prostate but predicting in bladder, despite different pathologists examining the different tissues. When training on one patient but testing on another, AUROC in bladder is 0.79±0.11 and in prostate is 0.96±0.04. Our tool is available at https://bitbucket.org/aschaumberg/deepscope.</p>","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"10477 ","pages":"42-58"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870882/pdf/nihms931049.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35962828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Learning Weighted Association Rules in Human Phenotype Ontology 人类表型本体的加权关联规则学习
P. Guzzi, Giuseppe Agapito, Marianna Milano, M. Cannataro
{"title":"Learning Weighted Association Rules in Human Phenotype Ontology","authors":"P. Guzzi, Giuseppe Agapito, Marianna Milano, M. Cannataro","doi":"10.1007/978-3-030-63061-4_22","DOIUrl":"https://doi.org/10.1007/978-3-030-63061-4_22","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"33 1","pages":"245-256"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88054646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Host Phenotype Prediction from Differentially Abundant Microbes Using RoDEO 利用RoDEO预测不同丰度微生物的宿主表型
A. Carrieri, N. Haiminen, L. Parida
{"title":"Host Phenotype Prediction from Differentially Abundant Microbes Using RoDEO","authors":"A. Carrieri, N. Haiminen, L. Parida","doi":"10.1007/978-3-319-67834-4_3","DOIUrl":"https://doi.org/10.1007/978-3-319-67834-4_3","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"13 1","pages":"27-41"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75814020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Ensemble Approaches for Stable Assessment of Clusters in Microbiome Samples 微生物组样品中聚类稳定性评估的集成方法
S. Brdar, V. Crnojevic
{"title":"Ensemble Approaches for Stable Assessment of Clusters in Microbiome Samples","authors":"S. Brdar, V. Crnojevic","doi":"10.1007/978-3-319-67834-4_16","DOIUrl":"https://doi.org/10.1007/978-3-319-67834-4_16","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"108 9 1","pages":"199-208"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81291646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance 进化的树突形态强调了结构突触输入对神经元性能的影响
Mohammad Ziyad Kagdi
{"title":"Evolving Dendritic Morphologies Highlight the Impact of Structured Synaptic Inputs on Neuronal Performance","authors":"Mohammad Ziyad Kagdi","doi":"10.1007/978-3-319-67834-4_18","DOIUrl":"https://doi.org/10.1007/978-3-319-67834-4_18","url":null,"abstract":"","PeriodicalId":92189,"journal":{"name":"Computational intelligence methods for bioinformatics and biostatistics : 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, revised selected papers. CIBB (Meeting) (13th : 2016 : Stirling, England)","volume":"33 1","pages":"220-234"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77764064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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