Using statistical and knowledge-based approaches for literature-based discovery.
about
Defrosting the digital library: bibliographic tools for the next generation web.Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseasesLiterature mining for the discovery of hidden connections between drugs, genes and diseasesIntegrated bio-entity network: a system for biological knowledge discoveryIdentifying novel drug indications through automated reasoningGraph theory enables drug repurposing--how a mathematical model can drive the discovery of hidden mechanisms of actionIdentifying plausible adverse drug reactions using knowledge extracted from the literatureMining the pharmacogenomics literature--a survey of the state of the artConcept similarity in publications precedes cross-disciplinary collaboration.Biomedical ontologies in action: role in knowledge management, data integration and decision support.Improving protein function prediction methods with integrated literature data.Mining connections between chemicals, proteins, and diseases extracted from Medline annotationsA graph-based recovery and decomposition of Swanson's hypothesis using semantic predications.Enriching plausible new hypothesis generation in PubMed.Advancing science through mining libraries, ontologies, and communities.Recent progress in automatically extracting information from the pharmacogenomic literature.Using information mining of the medical literature to improve drug safety.Context-driven automatic subgraph creation for literature-based discoveryFrontiers of biomedical text mining: current progress.Classification-by-Analogy: Using Vector Representations of Implicit Relationships to Identify Plausibly Causal Drug/Side-effect RelationshipsDrug repurposing and adverse event prediction using high-throughput literature analysis.Literature mining, ontologies and information visualization for drug repurposing.Supervised Learning Based Hypothesis Generation from Biomedical Literature.A quantitative model for linking two disparate sets of articles in MEDLINE.Application of Ferulic Acid for Alzheimer’s Disease: Combination of Text Mining and Experimental Validation.
P2860
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P2860
Using statistical and knowledge-based approaches for literature-based discovery.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh-hant
name
Using statistical and knowledge-based approaches for literature-based discovery.
@en
Using statistical and knowledge-based approaches for literature-based discovery.
@nl
type
label
Using statistical and knowledge-based approaches for literature-based discovery.
@en
Using statistical and knowledge-based approaches for literature-based discovery.
@nl
prefLabel
Using statistical and knowledge-based approaches for literature-based discovery.
@en
Using statistical and knowledge-based approaches for literature-based discovery.
@nl
P1476
Using statistical and knowledge-based approaches for literature-based discovery.
@en
P2093
Meliha Yetisgen-Yildiz
P304
P356
10.1016/J.JBI.2005.11.010
P50
P577
2006-01-04T00:00:00Z