標(biāo)題: Titlebook: Data Mining for Systems Biology; Methods and Protocol Hiroshi Mamitsuka,Charles DeLisi,Minoru Kanehisa Book 2013 Springer Science+Business [打印本頁(yè)] 作者: 軍械 時(shí)間: 2025-3-21 18:23
書目名稱Data Mining for Systems Biology影響因子(影響力)
書目名稱Data Mining for Systems Biology影響因子(影響力)學(xué)科排名
書目名稱Data Mining for Systems Biology網(wǎng)絡(luò)公開度
書目名稱Data Mining for Systems Biology網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining for Systems Biology被引頻次
書目名稱Data Mining for Systems Biology被引頻次學(xué)科排名
書目名稱Data Mining for Systems Biology年度引用
書目名稱Data Mining for Systems Biology年度引用學(xué)科排名
書目名稱Data Mining for Systems Biology讀者反饋
書目名稱Data Mining for Systems Biology讀者反饋學(xué)科排名
作者: 哀求 時(shí)間: 2025-3-21 22:13
,Discovering Interacting Domains and Motifs in Protein–Protein Interactions,o stimuli. These interactions are usually transient, easily formed, and disrupted, yet specific. Many of these transient interactions involve the binding of a protein domain to a short stretch (3–10) of amino acid residues, which can be characterized by a sequence pattern, i.e., .. We call these int作者: 兇兆 時(shí)間: 2025-3-22 04:13 作者: Anthrp 時(shí)間: 2025-3-22 08:23 作者: MILL 時(shí)間: 2025-3-22 10:14 作者: 敲竹杠 時(shí)間: 2025-3-22 14:20
Mining Regulatory Network Connections by Ranking Transcription Factor Target Genes Using Time Serieunderlying network. We present a technique addressing this problem through focussing on a more limited problem: inferring direct targets of a transcription factor from short expression time series. The method is based on combining Gaussian process priors and ordinary differential equation models all作者: 敲竹杠 時(shí)間: 2025-3-22 20:29 作者: 青少年 時(shí)間: 2025-3-22 21:42
Mining Frequent Subtrees in Glycan Data Using the Rings Glycan Miner Tool, the α-closed frequent subtree algorithm to find significant subtrees from within a data set of glycan structures, or carbohydrate sugar chains. The results are returned in order of .-value, which is computed based on the probability of the reproducibility of the returned structures. There is also a作者: 廢除 時(shí)間: 2025-3-23 04:11 作者: Fantasy 時(shí)間: 2025-3-23 08:22
Localization Prediction and Structure-Based In Silico Analysis of Bacterial Proteins: With Emphasis focus on β-barrel outer membrane proteins (BOMPs), describing and evaluating new tools for BOMP detection and topology prediction. Finally, we apply general protein structure prediction methods on these proteins to show that the structure of most BOMPs in . can be modeled reliably.作者: engrave 時(shí)間: 2025-3-23 10:43
,Analysis Strategy of Protein–Protein Interaction Networks,terfaces may lead to the development of many diseases. In this chapter, we will briefly introduce the background knowledge of the protein–protein interaction, followed by the detailed explanation of varied analysis—from basic to advanced, as well as related tools and databases. VisANT (.)—a free Web作者: AMBI 時(shí)間: 2025-3-23 14:56 作者: 支柱 時(shí)間: 2025-3-23 18:09 作者: 迅速飛過(guò) 時(shí)間: 2025-3-24 00:20 作者: 違反 時(shí)間: 2025-3-24 04:19
Genome-Wide Association Studies,have made genome-wide association (GWA) studies technically feasible. GWA studies help in the discovery and quantification of the genetic components of disease risks, many of which have not been unveiled before and have opened a new avenue to understanding disease, treatment, and prevention..This ch作者: 組裝 時(shí)間: 2025-3-24 09:49 作者: Terrace 時(shí)間: 2025-3-24 12:33
Molecular Network Analysis of Diseases and Drugs in KEGG, systemic functions of the cell, the organism, and the ecosystem. Major efforts have been undertaken for capturing and representing experimental knowledge as manually drawn KEGG pathway maps and for genome-based generalization of experimental knowledge through the KEGG Orthology (KO) system. Current作者: MIME 時(shí)間: 2025-3-24 16:23 作者: 財(cái)產(chǎn) 時(shí)間: 2025-3-24 19:45
https://doi.org/10.1007/978-3-663-07869-2o stimuli. These interactions are usually transient, easily formed, and disrupted, yet specific. Many of these transient interactions involve the binding of a protein domain to a short stretch (3–10) of amino acid residues, which can be characterized by a sequence pattern, i.e., .. We call these int作者: RAFF 時(shí)間: 2025-3-25 01:09 作者: 哄騙 時(shí)間: 2025-3-25 05:24 作者: 譏諷 時(shí)間: 2025-3-25 08:25
https://doi.org/10.1007/978-3-663-07869-2ortant challenge to gain insight on a cell’s working mechanisms. We present SIRENE, a method to estimate a GRN from a collection of expression data. Contrary to most existing methods for GRN inference, SIRENE requires as input a list of known regulations, in addition to expression data, and implemen作者: 鞭子 時(shí)間: 2025-3-25 13:40
https://doi.org/10.1007/978-3-663-07869-2underlying network. We present a technique addressing this problem through focussing on a more limited problem: inferring direct targets of a transcription factor from short expression time series. The method is based on combining Gaussian process priors and ordinary differential equation models all作者: doxazosin 時(shí)間: 2025-3-25 19:19
https://doi.org/10.1007/978-3-663-07869-2iological networks. Currently, the most comprehensive and validated biological networks are metabolic networks. Complete metabolic networks are easily sourced from multiple online databases. These databases reveal metabolic networks to be large, highly complex structures. This complexity is sufficie作者: LAP 時(shí)間: 2025-3-25 21:26 作者: 后來(lái) 時(shí)間: 2025-3-26 01:35 作者: Cloudburst 時(shí)間: 2025-3-26 06:00 作者: 全部逛商店 時(shí)間: 2025-3-26 12:09
https://doi.org/10.1007/978-3-663-07869-2terfaces may lead to the development of many diseases. In this chapter, we will briefly introduce the background knowledge of the protein–protein interaction, followed by the detailed explanation of varied analysis—from basic to advanced, as well as related tools and databases. VisANT (.)—a free Web作者: 女歌星 時(shí)間: 2025-3-26 16:22
https://doi.org/10.1007/978-3-663-07869-2sts of thousands of databases that were derived through computational inference of metabolic pathways from the MetaCyc pathway/genome database (PGDB). In some cases, these DBs underwent subsequent manual curation. Curated pathway DBs are now available for most of the major model organisms. Databases作者: integral 時(shí)間: 2025-3-26 17:48
https://doi.org/10.1007/978-3-663-07869-2already a common procedure in identifying biomarkers or signatures of phenotypic states such as diseases or compound treatments. However, in most of the cases, especially in complex diseases, even given a list of biomarkers, the underlying biological mechanisms are still obscure to us. In other word作者: 畢業(yè)典禮 時(shí)間: 2025-3-27 00:03
https://doi.org/10.1007/978-3-663-07869-2ach for constructing such functional linkage gene networks (FLNs) is based on the integration of diverse high-throughput functional genomics datasets. Data integration is a nontrivial task due to the heterogeneous nature of the different data sources and their variable accuracy and completeness. The作者: 江湖騙子 時(shí)間: 2025-3-27 02:47 作者: 易受刺激 時(shí)間: 2025-3-27 09:02 作者: 飛行員 時(shí)間: 2025-3-27 11:18
https://doi.org/10.1007/978-3-663-07869-2 systemic functions of the cell, the organism, and the ecosystem. Major efforts have been undertaken for capturing and representing experimental knowledge as manually drawn KEGG pathway maps and for genome-based generalization of experimental knowledge through the KEGG Orthology (KO) system. Current作者: 流逝 時(shí)間: 2025-3-27 16:06 作者: doxazosin 時(shí)間: 2025-3-27 18:31
https://doi.org/10.1007/978-3-663-07869-2sian network represents causal molecular mechanisms or statistical associations of the underlying system. Bayesian networks have been applied, for example, for inferring the structure of many biological networks from experimental data. We present some recent progress in learning the structure of static and dynamic Bayesian networks from data.作者: 滑稽 時(shí)間: 2025-3-27 22:25 作者: 叢林 時(shí)間: 2025-3-28 05:16
Hiroshi Mamitsuka,Charles DeLisi,Minoru KanehisaAids researchers in the further development of databases,mining,and visualization systems..Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice 作者: Instrumental 時(shí)間: 2025-3-28 07:38
Methods in Molecular Biologyhttp://image.papertrans.cn/d/image/262956.jpg作者: Gentry 時(shí)間: 2025-3-28 12:49 作者: 愛花花兒憤怒 時(shí)間: 2025-3-28 16:39 作者: aplomb 時(shí)間: 2025-3-28 21:08
https://doi.org/10.1007/978-1-62703-107-3Functional Inference; Network Inference; genotype; heterogeneous datasets; metabolism; nucleic acids; phen作者: BRAWL 時(shí)間: 2025-3-29 01:54
978-1-4939-5912-9Springer Science+Business Media New York 2013作者: 連詞 時(shí)間: 2025-3-29 05:30 作者: 策略 時(shí)間: 2025-3-29 09:08 作者: Terrace 時(shí)間: 2025-3-29 14:47 作者: DRILL 時(shí)間: 2025-3-29 19:10 作者: 財(cái)政 時(shí)間: 2025-3-29 22:23 作者: cavity 時(shí)間: 2025-3-30 01:00 作者: LVAD360 時(shí)間: 2025-3-30 07:02 作者: chemoprevention 時(shí)間: 2025-3-30 10:00
Dense Module Enumeration in Biological Networks,Given a weighted protein interaction network, our method discovers all protein sets that satisfy a user-defined minimum density threshold. We employ a reverse search strategy, which allows us to exploit the density criterion in an efficient way.作者: intertwine 時(shí)間: 2025-3-30 14:04
Mining Frequent Subtrees in Glycan Data Using the Rings Glycan Miner Tool, user-friendly manual that allows users to apply glycan array data from the Consortium for Functional Glycomics. Thus, glycobiologists can take the glycan structures that bind to a particular glycan-binding protein, for example, to retrieve the glycan subtrees that are deemed to be important for the binding to occur.作者: Liberate 時(shí)間: 2025-3-30 17:58 作者: 粗魯性質(zhì) 時(shí)間: 2025-3-30 23:38 作者: 過(guò)時(shí) 時(shí)間: 2025-3-31 02:56 作者: 對(duì)待 時(shí)間: 2025-3-31 07:08 作者: 浮夸 時(shí)間: 2025-3-31 11:54 作者: HAUNT 時(shí)間: 2025-3-31 13:24 作者: Counteract 時(shí)間: 2025-3-31 18:46 作者: 假裝是我 時(shí)間: 2025-3-31 23:02
https://doi.org/10.1007/978-3-663-07869-2es that maximizes the sequence and interaction similarities between matched nodes. We further suggest a novel evolutionary-based global alignment algorithm. We then compare the different methods on a yeast-fly-worm benchmark, discuss their performance differences, and conclude with open directions for future research.作者: 啞巴 時(shí)間: 2025-4-1 02:57
