標(biāo)題: Titlebook: Artificial Intelligence Methods and Tools for Systems Biology; Werner Dubitzky,Francisco Azuaje Book 2004 Springer Science+Business Media [打印本頁] 作者: emanate 時間: 2025-3-21 17:22
書目名稱Artificial Intelligence Methods and Tools for Systems Biology影響因子(影響力)
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書目名稱Artificial Intelligence Methods and Tools for Systems Biology被引頻次
書目名稱Artificial Intelligence Methods and Tools for Systems Biology被引頻次學(xué)科排名
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書目名稱Artificial Intelligence Methods and Tools for Systems Biology年度引用學(xué)科排名
書目名稱Artificial Intelligence Methods and Tools for Systems Biology讀者反饋
書目名稱Artificial Intelligence Methods and Tools for Systems Biology讀者反饋學(xué)科排名
作者: 知識 時間: 2025-3-21 22:10
QSAR Modeling of Mutagenicity on Non-Congeneric Sets of Organic Compounds,ods from artificial intelligence, quantum mechanics, statistical methods by analyzing relationships between the mutagenic activity of compounds and their structure. The overview is given on the use of artificial intelligence methods for the estimation of mutagenicity. The focus is on ., the selectio作者: progestin 時間: 2025-3-22 02:25
Characterizing Gene Expression Time Series using a Hidden Markov Model,terizing the developmental processes within the cell. By explicitly modelling the time dependent aspects of these data using a novel form of the HMM, each stage of cell development can be depicted. In this model, the hitherto unknown development process that manifests itself as changes in gene expre作者: OGLE 時間: 2025-3-22 05:00 作者: Orgasm 時間: 2025-3-22 09:19
A Data-Driven, Flexible Machine Learning Strategy for the Classification of Biomedical Data,es, they also present significant challenges for analysis, classification and interpretation. These challenges include sample sparsity, high-dimensional feature spaces, and noise/artifact signatures. Since a dataindependent ‘universal’ classifier does not exist, a classification strategy is needed, 作者: 隼鷹 時間: 2025-3-22 13:54
Cooperative Metaheuristics for Exploring Proteomic Data,pproximated solutions in a reasonable time. Cooperative metaheuristics are a sub-set of metaheuristics, which implies a parallel exploration of the search space by several entities with information exchange between them. Several improvements in the field of metaheuristics are given. A hierarchical a作者: 使糾纏 時間: 2025-3-22 20:14 作者: vasculitis 時間: 2025-3-22 22:29 作者: 成績上升 時間: 2025-3-23 04:06 作者: Terminal 時間: 2025-3-23 07:42 作者: 得罪人 時間: 2025-3-23 12:49
1568-2684 pments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain...As design blueprint, the book is intended for scientists and other professionals tasked wit作者: macrophage 時間: 2025-3-23 16:52 作者: Irremediable 時間: 2025-3-23 20:12
Derek D. Turner,Michelle I. Turnerrovide a state of the art overview. We present different possible definitions of ontology, examples of bio-ontologies and their use, formalisms that can be used to represent ontologies as well as tools that support the different stages in the life cycle of an ontology.作者: Nomogram 時間: 2025-3-24 02:03
hich the vast complexity and flexibility of life processes emerges. Here we review ways by which artificial intelligence approaches can help gaining a more quantitative understanding of regulatory genetic networks at the systems level.作者: 疏遠天際 時間: 2025-3-24 04:44 作者: 誹謗 時間: 2025-3-24 07:32 作者: interior 時間: 2025-3-24 12:17
Systems Level Modeling of Gene Regulatory Networks,hich the vast complexity and flexibility of life processes emerges. Here we review ways by which artificial intelligence approaches can help gaining a more quantitative understanding of regulatory genetic networks at the systems level.作者: Talkative 時間: 2025-3-24 16:00
Book 2004artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain...As design blueprint, the book is intended for scientists and other professionals tasked with developi作者: Entirety 時間: 2025-3-24 23:05
Lazy Learning for Predictive Toxicology based on a Chemical Ontology,esent chemical compounds, we introduce a new approach based on the chemical nomenclature to represent chemical compounds. In our experiments we show that both models, SAR and ontology-based, have comparable results for the predictive toxicology task.作者: 真繁榮 時間: 2025-3-25 02:52 作者: 高興一回 時間: 2025-3-25 05:01 作者: grudging 時間: 2025-3-25 08:30 作者: 褪色 時間: 2025-3-25 13:25
The Transition to Incipient Modern Algebra,ssion is represented by hidden concepts.We use clustering to learn probabilistic descriptions of these hidden concepts in terms of a .. Finally, we derive linguistic identifiers from the transition matrices that characterize the developmental processes. Such identifiers could be used to annotate a genome database to assist data retrieval.作者: COM 時間: 2025-3-25 17:43 作者: Tincture 時間: 2025-3-25 21:56 作者: gangrene 時間: 2025-3-26 01:26 作者: 美麗的寫 時間: 2025-3-26 08:06
Derek D. Turner,Michelle I. Turnerr development, and classifier aggregation/fusion. These components, which should be flexible, data-driven, extensible, and computationally efficient, must provide accurate, reliable diagnosis/prognosis with the fewest maximally discriminatory, yet medically interpretable, features.作者: 提名 時間: 2025-3-26 10:43 作者: PANG 時間: 2025-3-26 14:53 作者: 搖曳 時間: 2025-3-26 16:48
A Data-Driven, Flexible Machine Learning Strategy for the Classification of Biomedical Data,r development, and classifier aggregation/fusion. These components, which should be flexible, data-driven, extensible, and computationally efficient, must provide accurate, reliable diagnosis/prognosis with the fewest maximally discriminatory, yet medically interpretable, features.作者: aqueduct 時間: 2025-3-26 21:06 作者: oncologist 時間: 2025-3-27 02:49 作者: 狂怒 時間: 2025-3-27 08:54 作者: 慌張 時間: 2025-3-27 12:33 作者: GEON 時間: 2025-3-27 15:31
The Transition to Incipient Modern Algebra,terizing the developmental processes within the cell. By explicitly modelling the time dependent aspects of these data using a novel form of the HMM, each stage of cell development can be depicted. In this model, the hitherto unknown development process that manifests itself as changes in gene expre作者: 和藹 時間: 2025-3-27 21:29 作者: 鑲嵌細工 時間: 2025-3-28 01:05 作者: 凹處 時間: 2025-3-28 05:53 作者: AGOG 時間: 2025-3-28 09:05 作者: Explosive 時間: 2025-3-28 11:18
Derek D. Turner,Michelle I. Turnerteroperability between systems, and as query models and indexes to repositories of information. In this chapter we give a background of the area and provide a state of the art overview. We present different possible definitions of ontology, examples of bio-ontologies and their use, formalisms that c作者: 全等 時間: 2025-3-28 14:35
k of the cell. From a system level point of view, the various interactions and control loops, which form a genetic network, represent the basis upon which the vast complexity and flexibility of life processes emerges. Here we review ways by which artificial intelligence approaches can help gaining a作者: 緩解 時間: 2025-3-28 19:53
rocesses and working memory. We describe a computational neuroscience theoretical framework which shows how an attentional bias can influence perceptual processing, the mapping of sensory inputs to motor output and formation of selective working memory. This theoretical framework incorporates spikin作者: oracle 時間: 2025-3-29 00:59 作者: faucet 時間: 2025-3-29 06:43 作者: Hallowed 時間: 2025-3-29 10:14 作者: 晚間 時間: 2025-3-29 13:18
Computational Biologyhttp://image.papertrans.cn/b/image/162128.jpg作者: 蕁麻 時間: 2025-3-29 19:26
