標(biāo)題: Titlebook: Biomedical Literature Mining; Vinod D. Kumar,Hannah Jane Tipney Book 2014 Springer Science+Business Media New York 2014 biomedical literat [打印本頁] 作者: 小缺點(diǎn) 時(shí)間: 2025-3-21 18:31
書目名稱Biomedical Literature Mining影響因子(影響力)
書目名稱Biomedical Literature Mining影響因子(影響力)學(xué)科排名
書目名稱Biomedical Literature Mining網(wǎng)絡(luò)公開度
書目名稱Biomedical Literature Mining網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Biomedical Literature Mining被引頻次
書目名稱Biomedical Literature Mining被引頻次學(xué)科排名
書目名稱Biomedical Literature Mining年度引用
書目名稱Biomedical Literature Mining年度引用學(xué)科排名
書目名稱Biomedical Literature Mining讀者反饋
書目名稱Biomedical Literature Mining讀者反饋學(xué)科排名
作者: OATH 時(shí)間: 2025-3-21 23:49 作者: 切掉 時(shí)間: 2025-3-22 04:12
Partial Nondegenerate Finsler Spaceserminologies, ontologies, or databases representing these concepts. Though there has been a significant amount of research, there are still a limited number of practical, publicly available tools for concept mapping of biomedical text specified by the user as an independent task. In this chapter, se作者: liposuction 時(shí)間: 2025-3-22 04:49 作者: 鴕鳥 時(shí)間: 2025-3-22 08:51 作者: pulmonary 時(shí)間: 2025-3-22 14:03
, Algebras and?Modules: Unfiltered Case,e up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what 作者: dapper 時(shí)間: 2025-3-22 20:46
, Algebras and?Modules: Unfiltered Case,ut also proposing novel biomarker candidates is increasing rapidly for numerous clinically relevant disease areas. However, individual markers often lack sensitivity and specificity in the clinical context, resting essentially on the intra-individual phenotype variability hampering sensitivity, or o作者: 帳單 時(shí)間: 2025-3-23 01:09 作者: 打火石 時(shí)間: 2025-3-23 04:09
The Optical Lagrangian and the Ray Equation,l applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. Wh作者: Bouquet 時(shí)間: 2025-3-23 06:13
Some Basic Lagrangian Distributions,st engage in in order to understand emerging trends for scientific investment and strategy development. Developing trends analysis uses the number of publications within a 3-year window to determine concepts derived from well-established disease and gene ontologies to aid in recognizing and predicti作者: neutralize 時(shí)間: 2025-3-23 13:10
Lagrangian Probability Distributions,technological advances has further aggravated the data deluge. Seamless integration of the ever-increasing clinical, genomic, and experimental data and efficient mining for knowledge extraction, delivering actionable insight and generating testable hypotheses are therefore critical for the needs of 作者: 鞠躬 時(shí)間: 2025-3-23 16:00 作者: 失眠癥 時(shí)間: 2025-3-23 18:36 作者: Chagrin 時(shí)間: 2025-3-23 22:24 作者: excursion 時(shí)間: 2025-3-24 06:22 作者: 加劇 時(shí)間: 2025-3-24 10:10
https://doi.org/10.1007/978-3-319-53022-2The combination of scientific knowledge and experience is the key success for biomedical research. This chapter demonstrates some of the strategies used to help in identifying key opinion leaders with the expertise you need, thus enabling an effort to increase collaborative biomedical research.作者: Militia 時(shí)間: 2025-3-24 13:36 作者: ADOPT 時(shí)間: 2025-3-24 18:27 作者: Minatory 時(shí)間: 2025-3-24 22:58 作者: syring 時(shí)間: 2025-3-24 23:33 作者: 陰謀 時(shí)間: 2025-3-25 05:09
Methods in Molecular Biologyhttp://image.papertrans.cn/b/image/188071.jpg作者: Bureaucracy 時(shí)間: 2025-3-25 10:07
Book 2014itfalls..Authoritative and practical, .Biomedical Literature Mining.?is designed as a useful bioinformatics resource in biomedical literature text mining for both those long experienced in or entirely new to, the field..作者: 沖突 時(shí)間: 2025-3-25 13:05
Appendix: Numerical experiments,pproaches implemented by useful tools for information extraction and knowledge inference in the field of systems biology. We illustrate the practical utility of two online resources providing services of this type—namely, STRING and BioTextQuest—concluding with a discussion of current challenges and future perspectives in the field.作者: 閑逛 時(shí)間: 2025-3-25 17:08
Some Basic Lagrangian Distributions,rging trends at a relatively early stage and we analyze the literature-identified genes for genetic associations, druggability, and biological pathways to explore any potential biological connections between the two diseases that could be utilized for drug discovery.作者: BRUNT 時(shí)間: 2025-3-25 21:24
Biological Information Extraction and Co-occurrence Analysispproaches implemented by useful tools for information extraction and knowledge inference in the field of systems biology. We illustrate the practical utility of two online resources providing services of this type—namely, STRING and BioTextQuest—concluding with a discussion of current challenges and future perspectives in the field.作者: PIZZA 時(shí)間: 2025-3-26 00:18 作者: Precursor 時(shí)間: 2025-3-26 05:51 作者: 宣誓書 時(shí)間: 2025-3-26 12:22
Mining the Electronic Health Record for Disease Knowledgeining the EHR for disease knowledge and describes each step for data selection, preprocessing, transformation, data mining, and interpretation/validation. Topics including natural language processing, standards, and data privacy and security are also discussed in the context of this framework.作者: avulsion 時(shí)間: 2025-3-26 14:55
Physics of Earth and Space Environmentss. Here we present practical guidelines for constructing a text-mining pipeline from existing code and software components capable of extracting PPI networks from full-text articles. This approach can be adapted to tackle other types of biological network.作者: homocysteine 時(shí)間: 2025-3-26 18:13 作者: NOMAD 時(shí)間: 2025-3-26 23:57
Mining Biological Networks from Full-Text Articless. Here we present practical guidelines for constructing a text-mining pipeline from existing code and software components capable of extracting PPI networks from full-text articles. This approach can be adapted to tackle other types of biological network.作者: 很是迷惑 時(shí)間: 2025-3-27 03:31 作者: sclera 時(shí)間: 2025-3-27 05:54 作者: Rankle 時(shí)間: 2025-3-27 09:54
1064-3745 ation advice from the experts.Includes supplementary materia.Biomedical Literature Mining.,?discusses the multiple facets of modern biomedical literature mining and its many applications in genomics and systems biology. The volume is divided into three sections focusing on information retrieval, int作者: dendrites 時(shí)間: 2025-3-27 17:40 作者: 指派 時(shí)間: 2025-3-27 18:11 作者: VERT 時(shí)間: 2025-3-28 01:36 作者: echnic 時(shí)間: 2025-3-28 05:09
Accessing Biomedical Literature in the Current Information Landscapeccess is essential for several types of users including biomedical researchers, clinicians, database curators, and bibliometricians. In the past few decades, several online search tools and literature archives, generic as well as biomedicine specific, have been developed. We present this chapter in 作者: Innovative 時(shí)間: 2025-3-28 10:06 作者: Perennial長期的 時(shí)間: 2025-3-28 12:08 作者: 允許 時(shí)間: 2025-3-28 14:39
Biological Information Extraction and Co-occurrence Analysisl relationships then need to be detected. These relationships are typically detected by co-occurrence analysis, revealing associations between bioentities through their coexistence in single sentences and/or entire abstracts. These associations implicitly define networks, whose nodes represent terms作者: 一再遛 時(shí)間: 2025-3-28 19:04
Roles for Text Mining in Protein Function Predictione up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what 作者: 柏樹 時(shí)間: 2025-3-28 23:46
Functional Molecular Units for Guiding Biomarker Panel Designut also proposing novel biomarker candidates is increasing rapidly for numerous clinically relevant disease areas. However, individual markers often lack sensitivity and specificity in the clinical context, resting essentially on the intra-individual phenotype variability hampering sensitivity, or o作者: Biofeedback 時(shí)間: 2025-3-29 05:39 作者: Sedative 時(shí)間: 2025-3-29 08:38
Predicting Future Discoveries from Current Scientific Literaturel applications. Crossing of conceptual boundaries is often needed for groundbreaking biomedical research that generates highly inventive discoveries. We demonstrate the ability of a creative literature mining method to advance valuable new discoveries based on rare ideas from existing literature. Wh作者: 蘑菇 時(shí)間: 2025-3-29 15:20
Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discoveryst engage in in order to understand emerging trends for scientific investment and strategy development. Developing trends analysis uses the number of publications within a 3-year window to determine concepts derived from well-established disease and gene ontologies to aid in recognizing and predicti作者: filial 時(shí)間: 2025-3-29 18:20
Integrative Literature and Data Mining to Rank Disease Candidate Genestechnological advances has further aggravated the data deluge. Seamless integration of the ever-increasing clinical, genomic, and experimental data and efficient mining for knowledge extraction, delivering actionable insight and generating testable hypotheses are therefore critical for the needs of 作者: nonradioactive 時(shí)間: 2025-3-29 22:41 作者: CORD 時(shí)間: 2025-3-30 02:11
Systematic Drug Repurposing Through Text Miningss due to increased regulatory scrutiny, it is essential for pharmaceutical companies to maximize their return on investment by effectively extending drug life cycles. There have been many effective techniques, such as phenotypic screening and compound profiling, which identify new indications for e作者: 600 時(shí)間: 2025-3-30 06:13
Mining the Electronic Health Record for Disease Knowledge. In the past decade, there has been an increasing number of data and text mining studies focused on the identification of disease associations (e.g., disease–disease, disease–drug, and disease–gene) in structured and unstructured EHR data. This chapter presents a knowledge discovery framework for m作者: ATP861 時(shí)間: 2025-3-30 09:31
1064-3745 ul bioinformatics resource in biomedical literature text mining for both those long experienced in or entirely new to, the field..978-1-4939-5429-2978-1-4939-0709-0Series ISSN 1064-3745 Series E-ISSN 1940-6029 作者: CLASP 時(shí)間: 2025-3-30 13:08
Accessing Biomedical Literature in the Current Information Landscapetion describes current research and the state-of-the-art systems motivated by the challenges a user faces during query formulation and interpretation of search results. The research solutions are classified into five key areas related to text and data mining, text similarity search, semantic search,作者: 元音 時(shí)間: 2025-3-30 17:28 作者: MILL 時(shí)間: 2025-3-30 23:30 作者: 一窩小鳥 時(shí)間: 2025-3-31 02:54 作者: adequate-intake 時(shí)間: 2025-3-31 06:08
Functional Molecular Units for Guiding Biomarker Panel Designoach is to pick each marker as representative for a specific pathophysiological (mechanistic) process relevant for the disease under investigation, hence resulting in a multimarker panel for covering the set of pathophysiological processes underlying the frequently multifactorial composition of a cl作者: evaculate 時(shí)間: 2025-3-31 09:33
Predicting Future Discoveries from Current Scientific Literature Our literature-based discovery of NF-kappaB with its possible connections to autism was recently approved by scientific community, which confirms the ability of our literature mining methodology to accelerate future discoveries based on rare ideas from existing literature.作者: 慢慢沖刷 時(shí)間: 2025-3-31 15:09
Integrative Literature and Data Mining to Rank Disease Candidate Genesledge about a disease of interest to discover and rank novel candidate genes. In this chapter, we provide a brief overview of recent advances made in literature- and data-mining-based approaches for candidate gene prioritization. As a case study, we focus on a Web-based computational approach that u作者: Gyrate 時(shí)間: 2025-3-31 17:42 作者: Suggestions 時(shí)間: 2025-4-1 00:18
