標題: Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 11th International M Clelia DI Serio,Pietro Liò,Roberto Tagliaferr [打印本頁] 作者: 嚴厲 時間: 2025-3-21 20:09
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: Terrace 時間: 2025-3-21 20:31
Grundbegriffe der deskriptiven Statistik,mators. In the context of Gaussian graphical modeling, we compare the proposed estimator to the graphical lasso. This work is a brief exposé of the technical developments in [1], focussing on applications in gene-gene interaction network reconstruction.作者: 膝蓋 時間: 2025-3-22 01:00
https://doi.org/10.1007/978-3-319-24462-4evolutionary algorithms; gene ontology; image analysis; machine learning; parallel computing; association作者: 發(fā)微光 時間: 2025-3-22 05:51 作者: 鎮(zhèn)痛劑 時間: 2025-3-22 09:36
https://doi.org/10.1007/978-3-8348-9110-5on of a biological concept that is associated to one or more gene products through a process also known as annotation. Each annotation may be derived using different methods and an Evidence Code (EC) takes into account of this process. The importance and the specificity of both GO terms and annotati作者: 修剪過的樹籬 時間: 2025-3-22 16:05 作者: 修剪過的樹籬 時間: 2025-3-22 17:07 作者: 攝取 時間: 2025-3-22 22:37 作者: BINGE 時間: 2025-3-23 02:43
Grundbegriffe der deskriptiven Statistik,longing to the same group are more similar between each other than items in different groups. Consensus clustering is a methodology for combining different clustering solutions from the same data set in a new clustering, in order to obtain a more accurate and stable solution. In this work we compare作者: 甜食 時間: 2025-3-23 05:53
,Urnen- und Teilchen/F?cher-Modelle,xpert, are now subjected to computational analytics. The use of machine learning techniques allows one to extend the computational imaging approach by considering various markers based on DNA, mRNA, microRNA (miRNA) and proteins that could be used for classification of disease taxonomy, response to 作者: N防腐劑 時間: 2025-3-23 11:49
,Endliche Wahrscheinlichkeitsr?ume, number of samples (. patients) and a large number of genes (. predictors). Therefore, the main challenge is to cope with the high-dimensionality. Moreover, genes are co-regulated and their expression levels are expected to be highly correlated. In order to face these two issues, network based appro作者: 傀儡 時間: 2025-3-23 16:25
Zufallsexperimente, Ergebnismengen,tor of fixed length. This simple process allows to compare sequences in an alignment free way, using common similarities and distance functions on the numerical codomain of the mapping. The most common used decomposition uses all the substrings of a fixed length . making the codomain of exponential 作者: 溫室 時間: 2025-3-23 21:07 作者: CRAFT 時間: 2025-3-24 00:21
https://doi.org/10.1007/978-3-8348-9465-6 it is a sequence of permutations of a length–. string. In this paper, we define an approximate variant of Abelian periods which allows variations between adjacent elements of the sequence. Particularly, we compare two adjacent elements in the sequence using .– and .– metrics. We develop an algorith作者: 宣稱 時間: 2025-3-24 03:08
,Urnen- und Teilchen/F?cher-Modelle,f gene regulatory networks and human diseases. This problem becomes even more challenging when network models and algorithms have to take into account slightly significant effects, caused by often peripheral or unknown genes that cooperatively cause the observed diseased phenotype. Many solutions, f作者: 擋泥板 時間: 2025-3-24 09:51
Zufallsexperimente, Ergebnismengen,ve means to explore the transcriptome of an organism of interest. However, interpreting this extremely large data coming out from RNA-Seq into biological knowledge is a problem, and biologist-friendly tools to analyze them are lacking. In our lab, we develop a Transcriptator web application based on作者: CHASE 時間: 2025-3-24 14:38
Grundbegriffe der deskriptiven Statistik,mators. In the context of Gaussian graphical modeling, we compare the proposed estimator to the graphical lasso. This work is a brief exposé of the technical developments in [1], focussing on applications in gene-gene interaction network reconstruction.作者: 悲觀 時間: 2025-3-24 18:53
Grundbegriffe der deskriptiven Statistik,rsome. A simpler alternative which does not require specific software packages could be fitting a penalized piecewise exponential model. In this work the implementation of such strategy in WinBUGS is illustrated, and preliminary results are reported concerning the application of Bayesian P-splines t作者: Common-Migraine 時間: 2025-3-24 21:00
,Urnen- und Teilchen/F?cher-Modelle,sets. The novelty of this paper arises in the use of q-values to pre-filter the features of a DNA microarray dataset identifying the most significant ones and including this information into a genetic algorithm for further feature selection. This method is applied to a lung cancer microarray dataset作者: 委屈 時間: 2025-3-25 02:15
Clelia DI Serio,Pietro Liò,Roberto TagliaferriIncludes supplementary material: 作者: MAZE 時間: 2025-3-25 05:27
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232384.jpg作者: 流動才波動 時間: 2025-3-25 09:34 作者: 出來 時間: 2025-3-25 15:15
Conference proceedings 2015 Bioinformatics and Biostatistics, CIBB 2014, held in Cambridge, UK, in June 2014..The 25 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers focus problems concerning computational techniques in bioinformatics, systems biology, medical informatics and biostatistics..作者: Endoscope 時間: 2025-3-25 17:17
GO-WAR: A Tool for Mining Weighted Association Rules from Gene Ontology Annotationson of a biological concept that is associated to one or more gene products through a process also known as annotation. Each annotation may be derived using different methods and an Evidence Code (EC) takes into account of this process. The importance and the specificity of both GO terms and annotati作者: investigate 時間: 2025-3-25 21:14
Extended Spearman and Kendall Coefficients for Gene Annotation List Correlational machine learning algorithms are available in this domain; they include relevant parameters that might influence the output list of predicted gene annotations. The amount that the variation of these key parameters affect the output gene annotation lists remains an open aspect to be evaluated. Here作者: Outshine 時間: 2025-3-26 03:58
Statistical Analysis of Protein Structural Features: Relationships and PCA Groupingng novel and strengthened methods to investigate in deep protein structure, and to analyze conformational features, in order to highlight relationships to functional properties. We selected some protein families based on their different structural class from CATH database, and studied in detail many作者: 誹謗 時間: 2025-3-26 07:10 作者: FECK 時間: 2025-3-26 10:25
Consensus Clustering in Gene Expressionlonging to the same group are more similar between each other than items in different groups. Consensus clustering is a methodology for combining different clustering solutions from the same data set in a new clustering, in order to obtain a more accurate and stable solution. In this work we compare作者: humectant 時間: 2025-3-26 14:37
Automated Detection of Fluorescent Probes in Molecular Imagingxpert, are now subjected to computational analytics. The use of machine learning techniques allows one to extend the computational imaging approach by considering various markers based on DNA, mRNA, microRNA (miRNA) and proteins that could be used for classification of disease taxonomy, response to 作者: rheumatism 時間: 2025-3-26 20:02 作者: inspired 時間: 2025-3-26 22:38 作者: 發(fā)生 時間: 2025-3-27 03:02
Detecting Overlapping Protein Communities in Disease Networksative and the semantic information, that we call . method. We applied . in analyzing Protein-protein interactions (.) networks of . infection and Leukemia in Homo sapiens. . found significant overlapping biological communities. In particular, it found a strong relationship between . and Leukemia as 作者: 晚間 時間: 2025-3-27 08:30
Approximate Abelian Periods to Find Motifs in Biological Sequences it is a sequence of permutations of a length–. string. In this paper, we define an approximate variant of Abelian periods which allows variations between adjacent elements of the sequence. Particularly, we compare two adjacent elements in the sequence using .– and .– metrics. We develop an algorith作者: Mortal 時間: 2025-3-27 12:16
Sem Best Shortest Paths for the Characterization of Differentially Expressed Genesf gene regulatory networks and human diseases. This problem becomes even more challenging when network models and algorithms have to take into account slightly significant effects, caused by often peripheral or unknown genes that cooperatively cause the observed diseased phenotype. Many solutions, f作者: Petechiae 時間: 2025-3-27 15:18 作者: 南極 時間: 2025-3-27 19:28 作者: 凈禮 時間: 2025-3-28 00:47 作者: 防水 時間: 2025-3-28 05:18 作者: PALMY 時間: 2025-3-28 06:56
https://doi.org/10.1007/978-3-8348-9110-5e rules with low IC. This paper presents a methodology for extracting Weighted Association Rules from GO implemented in a tool named GO-WAR (Gene Ontology-based Weighted Association Rules). It is able to extract association rules with a high level of IC without loss of Support and Confidence from a 作者: HALL 時間: 2025-3-28 13:48 作者: 桉樹 時間: 2025-3-28 15:40
Zufallsexperimente, Ergebnismengen,sed quantitative measure for DNA sequence specificity that we have recently introduced in the literature. Results computed on public datasets show the effectiveness of the proposed feature selection method.作者: 溫順 時間: 2025-3-28 20:43 作者: 爆炸 時間: 2025-3-29 01:01 作者: 法律 時間: 2025-3-29 05:21
The General Regression Neural Network to Classify Barcode and mini-barcode DNA作者: Capture 時間: 2025-3-29 11:11 作者: cylinder 時間: 2025-3-29 14:53 作者: 女上癮 時間: 2025-3-29 17:50 作者: 最高峰 時間: 2025-3-29 22:18
A New Feature Selection Methodology for K-mers Representation of DNA Sequencessed quantitative measure for DNA sequence specificity that we have recently introduced in the literature. Results computed on public datasets show the effectiveness of the proposed feature selection method.作者: 相符 時間: 2025-3-30 02:22 作者: 性滿足 時間: 2025-3-30 08:04
Zufallsexperimente, Ergebnismengen,tasets of different organisms’ genes, showed interesting patterns between the predicted lists. Additionally, they allowed expressing some useful considerations about the prediction parameters and algorithms used.作者: 散布 時間: 2025-3-30 11:59
,Urnen- und Teilchen/F?cher-Modelle,e summaries with different ontologies a set of descriptor terms is derived and compared in order to obtain a measure of relatedness within the bio-organizations we considered. Finally, the most important annotations within each family are extracted using a text categorization method.作者: 書法 時間: 2025-3-30 12:38
,Urnen- und Teilchen/F?cher-Modelle,rphase nuclei and record the positions of different coloured probes attached to chromatin regions within these nuclei. Our method could be used for obtaining information such as pairwise distances between probes and inferring properties of chromatin structure.作者: SPECT 時間: 2025-3-30 20:19
,Urnen- und Teilchen/F?cher-Modelle, shortest paths between differentially expressed genes in biological interaction networks, with absolutely no need of user-defined parameters or heuristic rules, enabling a free-of-bias discovery and overcoming common issues affecting the most recent network-based algorithms.作者: 里程碑 時間: 2025-3-30 23:50
Extended Spearman and Kendall Coefficients for Gene Annotation List Correlationtasets of different organisms’ genes, showed interesting patterns between the predicted lists. Additionally, they allowed expressing some useful considerations about the prediction parameters and algorithms used.作者: 一個姐姐 時間: 2025-3-31 03:11 作者: garrulous 時間: 2025-3-31 07:38
Automated Detection of Fluorescent Probes in Molecular Imagingrphase nuclei and record the positions of different coloured probes attached to chromatin regions within these nuclei. Our method could be used for obtaining information such as pairwise distances between probes and inferring properties of chromatin structure.作者: Addictive 時間: 2025-3-31 10:57
Sem Best Shortest Paths for the Characterization of Differentially Expressed Genes shortest paths between differentially expressed genes in biological interaction networks, with absolutely no need of user-defined parameters or heuristic rules, enabling a free-of-bias discovery and overcoming common issues affecting the most recent network-based algorithms.作者: Canvas 時間: 2025-3-31 13:55
Conference proceedings 2015 Bioinformatics and Biostatistics, CIBB 2014, held in Cambridge, UK, in June 2014..The 25 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers focus problems concerning computational techniques in bioinformatics, systems biology, medical informatics and 作者: 輕快帶來危險 時間: 2025-3-31 20:09
0302-9743 rs presented were carefully reviewed and selected from 44 submissions. The papers focus problems concerning computational techniques in bioinformatics, systems biology, medical informatics and biostatistics..978-3-319-24461-7978-3-319-24462-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
