about
OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expressionMedEvi: retrieving textual evidence of relations between biomedical concepts from MedlineContent-rich biological network constructed by mining PubMed abstractsLAITOR--Literature Assistant for Identification of Terms co-Occurrences and RelationshipsLarge-scale directional relationship extraction and resolutionConstruction of an annotated corpus to support biomedical information extractionLinguistic feature analysis for protein interaction extractionEnriching a biomedical event corpus with meta-knowledge annotation.Text mining of full-text journal articles combined with gene expression analysis reveals a relationship between sphingosine-1-phosphate and invasiveness of a glioblastoma cell line.Comparative analysis of five protein-protein interaction corporaMetNet: Software to Build and Model the Biogenetic Lattice of Arabidopsis.Identification and analysis of co-occurrence networks with NetCutter.All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learningA realistic assessment of methods for extracting gene/protein interactions from free text.PathBinder--text empirics and automatic extraction of biomolecular interactionsISDB: Interaction Sentence Database.A comprehensive benchmark of kernel methods to extract protein-protein interactions from literatureRanking gene-drug relationships in biomedical literature using Latent Dirichlet AllocationA detailed error analysis of 13 kernel methods for protein-protein interaction extraction.On the efficacy of per-relation basis performance evaluation for PPI extraction and a high-precision rule-based approachPotential therapeutic targets for oral cancer: ADM, TP53, EGFR, LYN, CTLA4, SKIL, CTGF, CD70.Approximate subgraph matching-based literature mining for biomedical events and relationsAutomatic extraction of biomolecular interactions: an empirical approachProtein-protein interaction extraction with feature selection by evaluating contribution levels of groups consisting of related features.Corpus refactoring: a feasibility studyMETSP: a maximum-entropy classifier based text mining tool for transporter-substrate identification with semistructured textA Review of Recent Advancement in Integrating Omics Data with Literature Mining towards Biomedical Discoveries.NLP-based information extraction for managing the molecular biology literature.An analysis on the entity annotations in biological corpora.Extraction of Protein-Protein Interaction from Scientific Articles by Predicting Dominant Keywords.Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.Deep learning with word embeddings improves biomedical named entity recognition.PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.Constructing Genetic Networks using Biomedical Literature and Rare Event Classification.Exploiting and assessing multi-source data for supervised biomedical named entity recognition.Linked open data-based framework for automatic biomedical ontology generation
P2860
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P2860
description
2002 nî lūn-bûn
@nan
2002年の論文
@ja
2002年論文
@yue
2002年論文
@zh-hant
2002年論文
@zh-hk
2002年論文
@zh-mo
2002年論文
@zh-tw
2002年论文
@wuu
2002年论文
@zh
2002年论文
@zh-cn
name
Mining MEDLINE: abstracts, sentences, or phrases?
@en
Mining MEDLINE: abstracts, sentences, or phrases?
@nl
type
label
Mining MEDLINE: abstracts, sentences, or phrases?
@en
Mining MEDLINE: abstracts, sentences, or phrases?
@nl
prefLabel
Mining MEDLINE: abstracts, sentences, or phrases?
@en
Mining MEDLINE: abstracts, sentences, or phrases?
@nl
P2093
P1476
Mining MEDLINE: abstracts, sentences, or phrases?
@en
P2093
P304
P577
2002-01-01T00:00:00Z