標(biāo)題: Titlebook: Data Integration in the Life Sciences; 7th International Co Patrick Lambrix,Graham Kemp Conference proceedings 2010 Springer-Verlag Berlin [打印本頁] 作者: 轉(zhuǎn)變 時(shí)間: 2025-3-21 17:06
書目名稱Data Integration in the Life Sciences影響因子(影響力)
書目名稱Data Integration in the Life Sciences影響因子(影響力)學(xué)科排名
書目名稱Data Integration in the Life Sciences網(wǎng)絡(luò)公開度
書目名稱Data Integration in the Life Sciences網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Integration in the Life Sciences被引頻次
書目名稱Data Integration in the Life Sciences被引頻次學(xué)科排名
書目名稱Data Integration in the Life Sciences年度引用
書目名稱Data Integration in the Life Sciences年度引用學(xué)科排名
書目名稱Data Integration in the Life Sciences讀者反饋
書目名稱Data Integration in the Life Sciences讀者反饋學(xué)科排名
作者: 有毛就脫毛 時(shí)間: 2025-3-21 23:58 作者: Delirium 時(shí)間: 2025-3-22 00:47 作者: deactivate 時(shí)間: 2025-3-22 07:33 作者: 精確 時(shí)間: 2025-3-22 11:13 作者: 大猩猩 時(shí)間: 2025-3-22 16:28
On the Secure Sharing and Aggregation of Data to Support Systems Biology Researchciplines. In particular, the ‘data explosion’ problem associated with the Life Sciences has been recognised by many researchers and commented upon widely, as have the associated data management problems. In this paper we describe how a middleware framework that supports the secure sharing and aggreg作者: 大猩猩 時(shí)間: 2025-3-22 18:12
Helping Biologists Effectively Build Workflows, without Programmingvailable within Seahawk, the Daggoo system helps users adapt forms on existing Web sites to Moby’s specifications. Biologists were interviewed and given workflow design tasks, which revealed the types of tools present in their conceptual analysis workflows, and the types of control flow they underst作者: 高原 時(shí)間: 2025-3-22 23:30 作者: Coeval 時(shí)間: 2025-3-23 05:19 作者: 火海 時(shí)間: 2025-3-23 06:24
Algorithm for Grounding Mutation Mentions from Text to Protein Sequences important subfield of bioinformatics for which mutation grounding is a critical step. Presented here is a method for grounding of textual mentions from papers describing mutational changes to proteins. We distinguish between grounding of mutation entities to protein database identifiers and to the 作者: 神化怪物 時(shí)間: 2025-3-23 11:37
Handling Missing Features with Boosting Algorithms for Protein–Protein Interaction Predictiono a feature vector for classification. However, missing values in the data can impact on the prediction accuracy. Boosting has emerged as a powerful tool for feature selection and classification. Bayesian methods have traditionally been used to cope with missing data, with boosting being applied to 作者: 教義 時(shí)間: 2025-3-23 16:48 作者: 莊嚴(yán) 時(shí)間: 2025-3-23 19:50 作者: 勛章 時(shí)間: 2025-3-23 23:03
An Integration Architecture Designed to Deal with the Issues of Biological Scope, Scale and Complexies of complex biological data. It does this by providing: adaptable software which enables interoperable data access; a step-wise and flexible integration strategy, allowing new information to be overlaid on top of existing annotations and context graphs; and through the provision of asynchronous me作者: peak-flow 時(shí)間: 2025-3-24 03:16
Quality Assessment of MAGE-ML Genomic Datasets Using DescribeXn of experiment conclusions and enabling researchers to access and reuse a growing body of gene expression knowledge. While there are several data-exchange standards, numerous microarray experiment datasets are published using the MAGE-ML XML schema. Assessing the quality of published experiments is作者: 商談 時(shí)間: 2025-3-24 08:31
Search Computing: Integrating Ranked Data in the Life Sciences, in search computing, search services provide ranked answers to requests, and mechanisms are provided for integrating results from multiple searches. This paper presents a case study of the use of a domain independent search computing platform for describing well known bioinformatics resources as s作者: ALLEY 時(shí)間: 2025-3-24 12:28
0302-9743 DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and978-3-642-15119-4978-3-642-15120-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: saturated-fat 時(shí)間: 2025-3-24 15:09
Conference proceedings 2010iques can address requirements identi?ed in the life sciences. DILS 2010 was the seventh event in the series and was held in Goth- burg, Sweden during August 25–27, 2010. The associated proceedings contain 14 peer-reviewed papers and 2 invited papers. The sessions addressed ontology engineering, and作者: 搜尋 時(shí)間: 2025-3-24 20:40 作者: 鞏固 時(shí)間: 2025-3-25 01:17 作者: 殘暴 時(shí)間: 2025-3-25 04:38
https://doi.org/10.1007/978-1-4471-5107-4exploit their advantages in a new hybrid approach. The data are extracted from the original data sources using SB-KOM (System Biology Khaos Ontology-based Mediator) and then stored locally in the data warehouse to ensure a fast performance and data consistency.作者: 舊石器時(shí)代 時(shí)間: 2025-3-25 07:42 作者: Bombast 時(shí)間: 2025-3-25 14:19
0302-9743 throughput experimental methods in the life sciences is giving rise to numerous large, c- plex and valuable data resources. This foundation of experimental data und- pins the systematic study of organismsand diseases, which increasinglydepends on the development of models of biological systems. The 作者: myalgia 時(shí)間: 2025-3-25 18:42
https://doi.org/10.1007/978-1-84996-241-4Biology research at the University of Oxford. As well as giving an overview of the framework and its application, we attempt to set our work within the wider context of the emerging challenges associated with data sharing within the Life Sciences.作者: 擴(kuò)大 時(shí)間: 2025-3-25 23:30
An Educational Virtualization Infrastructure comparisons and from gene expression results can be integrated in a way that takes account of the ranked results from the different types of data. In so doing, the paper illustrates the use of ranking as a first class citizen for data integration in the life sciences, and identifies open issues for further investigation.作者: 隱藏 時(shí)間: 2025-3-26 01:54
On the Secure Sharing and Aggregation of Data to Support Systems Biology ResearchBiology research at the University of Oxford. As well as giving an overview of the framework and its application, we attempt to set our work within the wider context of the emerging challenges associated with data sharing within the Life Sciences.作者: obeisance 時(shí)間: 2025-3-26 05:13
Search Computing: Integrating Ranked Data in the Life Sciences comparisons and from gene expression results can be integrated in a way that takes account of the ranked results from the different types of data. In so doing, the paper illustrates the use of ranking as a first class citizen for data integration in the life sciences, and identifies open issues for further investigation.作者: 離開 時(shí)間: 2025-3-26 09:44 作者: PALMY 時(shí)間: 2025-3-26 14:34 作者: 獸群 時(shí)間: 2025-3-26 19:37 作者: Exclude 時(shí)間: 2025-3-27 00:02
Computer Communications and Networkscorrect grounding to a protein sequence, independent of a protein-mutation tuple extraction task. Using a gold standard corpus of full text articles and corresponding protein sequences we show high performance precision and recall and discuss novel aspects of the algorithm in the context of previous work.作者: NAUT 時(shí)間: 2025-3-27 01:40 作者: 遺傳學(xué) 時(shí)間: 2025-3-27 09:19 作者: 生命層 時(shí)間: 2025-3-27 10:06 作者: 放棄 時(shí)間: 2025-3-27 13:37
The Cinderella of Biological Data Integration: Addressing Some of the Challenges of Entity and Relatf targets not specified in titles and false-positives from non-target proteins in titles. We also examined the time-signals for selected target and non-target names by year of patent publication. Our results exemplify problems and some solutions for extracting data from this source.作者: 耐寒 時(shí)間: 2025-3-27 18:44 作者: 進(jìn)入 時(shí)間: 2025-3-28 00:51
An Integration Architecture Designed to Deal with the Issues of Biological Scope, Scale and Complexi across heterogeneous data from approximately 20,000 patient samples.?Addama supports projects like the TCGA through accepting that biological understanding continually changes, and that the rapid integration of new information and analyses is an essential requirement when supporting research.作者: 沙文主義 時(shí)間: 2025-3-28 02:52
https://doi.org/10.1007/978-1-60327-365-7provide building blocks for large scale, high-performance analytical image exploration systems, through rich metadata models, comprehensive query and data access capabilities, and efficient database and HPC support.作者: 昏睡中 時(shí)間: 2025-3-28 07:11
Isolation and Culture Techniquesns impossible. We therefore propose an approach to automatically discover evolving or stable ontology regions. We evaluate the approach by studying evolving regions in the Gene Ontology and the NCI Thesaurus.作者: initiate 時(shí)間: 2025-3-28 12:21 作者: 有害處 時(shí)間: 2025-3-28 17:19 作者: 陶瓷 時(shí)間: 2025-3-28 21:04
https://doi.org/10.1007/978-3-658-20967-4tained output pages of the related data sources, by query probing using . identified input instances. Then, using a hierarchical representation of schemas and by applying clustering techniques, we are able to generate schema matches. We show the effectiveness of our technique while integrating 24 query interfaces.作者: 拒絕 時(shí)間: 2025-3-28 23:16
Christian Dremel,Matthias Herteriching, or at least minimizing the manual effort required during, creation of quantitative models from qualitative models and experimental data. Automating the process makes model construction more systematic, supports good practice at all stages in the pipeline, and allows timely integration of high throughput experimental results into models.作者: headway 時(shí)間: 2025-3-29 07:01 作者: 悲痛 時(shí)間: 2025-3-29 07:35 作者: 千篇一律 時(shí)間: 2025-3-29 11:38
Discovering Evolving Regions in Life Science Ontologiesns impossible. We therefore propose an approach to automatically discover evolving or stable ontology regions. We evaluate the approach by studying evolving regions in the Gene Ontology and the NCI Thesaurus.作者: 寬容 時(shí)間: 2025-3-29 15:47
On Matching Large Life Science Ontologies in Paralleld intra-matcher parallelism as well as the parallel execution of element- and structure-level matching. We implemented a distributed infrastructure for parallel ontology matching and evaluate different approaches for parallel matching of large life science ontologies in the field of anatomy and molecular biology.作者: 謊言 時(shí)間: 2025-3-29 20:57 作者: venous-leak 時(shí)間: 2025-3-30 00:15
Instance Discovery and Schema Matching with Applications to Biological Deep Web Data Integrationtained output pages of the related data sources, by query probing using . identified input instances. Then, using a hierarchical representation of schemas and by applying clustering techniques, we are able to generate schema matches. We show the effectiveness of our technique while integrating 24 query interfaces.作者: 恃強(qiáng)凌弱的人 時(shí)間: 2025-3-30 04:36 作者: STIT 時(shí)間: 2025-3-30 08:46
https://doi.org/10.1007/978-3-642-15120-0biochemical systems; biological ontologies; data mining; information management; knowledge discovery; ont作者: 緊張過度 時(shí)間: 2025-3-30 15:56 作者: 事物的方面 時(shí)間: 2025-3-30 17:05
Provenance Management for Data Explorationecedented volume of data acquired by sensors, derived by simulations and analysis processes, and shared on the Web opens up new opportunities, but it also creates many challenges when it comes to managing and analyzing these data.作者: 整潔 時(shí)間: 2025-3-30 23:43 作者: 營養(yǎng) 時(shí)間: 2025-3-31 01:29 作者: flaunt 時(shí)間: 2025-3-31 08:49 作者: 吼叫 時(shí)間: 2025-3-31 13:07
https://doi.org/10.1007/978-1-60327-365-7tems. However, most of the information available in biomedical images remains underutilized in research projects. In this paper, we discuss the requirements and design of system support for composing, executing, and exploring in silico experiments involving microscopy images. This framework aims to 作者: Judicious 時(shí)間: 2025-3-31 14:58 作者: 周興旺 時(shí)間: 2025-3-31 19:46 作者: Ringworm 時(shí)間: 2025-4-1 00:37
Tools and Technologies for Building Cloudsogies is not an easy task and the resulting ontologies may have defects affecting the results of ontology-based data integration and retrieval. In this paper we present a system for debugging ontologies regarding an important kind of modeling defects. Our system supports a domain expert to detect an作者: expository 時(shí)間: 2025-4-1 02:53 作者: refine 時(shí)間: 2025-4-1 09:22 作者: overshadow 時(shí)間: 2025-4-1 13:07
https://doi.org/10.1007/978-1-4471-5107-4ledge. Even though data integration can provide solutions to such biological problems, it is often problematic due to the sources’ heterogeneity and their semantic and structural diversity. Moreover, necessary updates of both structure and content of databases provide further challenges for an integ
