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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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Enzyminer. Resource Report Resource Website 1+ mentions |
Enzyminer. (RRID:SCR_006241) | production service resource, database, service resource, data or information resource | EnzyMiner automatically identifies the PubMed abstracts that contain information on the impact of a protein level mutation on the stability or the activity of a given enzyme. For querying EnzyMiner, please choose an enzyme from the list and specify if you are interested in disease related abstracts or non-disease related abstracts. For disease related abstracts, the mutation list and direct links to the abstracts will be displayed. For those abstracts that are related to non-diseases, in addition to having the mutation list, the abstracts are also categorized into two groups. These two groups determine whether the mutation has an effect on the enzyme''s stability or functionality. If your target enzyme is not in the list, please write the enzyme name to the query box. We will run the EnzyMiner for the desired enzyme and add the results to our database. EnzyMiner has been developed by Computational Biology Lab of Sabanci University. | has parent organization: Sabanci University; Istanbul; Turkey | PMID:19758466 | nif-0000-06673 | SCR_006241 | 2026-08-13 09:27:27 | 2 | ||||||||||
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PANOGA Resource Report Resource Website 1+ mentions |
PANOGA (RRID:SCR_006242) | PANOGA | production service resource, data analysis service, service resource, analysis service resource | A web server to devise functionally important pathways through the identification of single nucleotide polymorphism (SNP)-targeted genes within these pathways. The strength of the methodology stems from its multidimensional perspective, where evidence from the following five resources is combined: (i) genetic association information obtained through GWAS, (ii) SNP functional information, (iii) protein-protein interaction network, (iv) linkage disequilibrium and (v) biochemical pathways. | single nucleotide polymorphism, genome-wide association study, pathway, function, gene, genetic association, protein-protein interaction network, linkage disequilibrium, protein-protein interaction |
is listed by: OMICtools has parent organization: Sabanci University; Istanbul; Turkey |
PMID:24413675 | Free, Public, Free for academic use, (source code upon request) | OMICS_02238 | SCR_006242 | Pathway and Network-Oriented GWAS Analysis, Pathway and Network Oriented GWAS (Genome-Wide Association Study) Analysis, Pathway and Network Oriented GWAS Analysis | 2026-08-13 09:27:27 | 7 | ||||||
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Haldanes Sieve Resource Report Resource Website 1+ mentions |
Haldanes Sieve (RRID:SCR_007178) | Haldane?s Sieve | data or information resource, blog, narrative resource | Blog discussing preprints in population and evolutionary genetics. | is listed by: OMICtools | OMICS_01714 | SCR_007178 | 2026-08-13 09:27:40 | 3 | ||||||||||
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FaceBase Biorepository Resource Report Resource Website 1+ mentions |
FaceBase Biorepository (RRID:SCR_006001) | FaceBase Biorepository | material resource, tissue bank, biomaterial supply resource | THIS RESOURCE IS NO LONGER IN SERVICE,documented on January,18, 2022. FaceBase Biorepository is now collecting biological samples from people with cleft lip/palate and their family members. Information for Prospective Cases: Clefts of the lip and/or palate can be caused by a wide range of genetic, environmental and other factors. The FaceBase Biorepository will serve as a common source of both biological samples and information that can be made available to investigators trying to determine the underlying cause of these common birth defects. Genetic studies, in particular, will benefit from both family history information and having samples from affected individuals as well as their family members. DNA is the information containing molecules found in all the cells of our body and can be easily obtained from material such as blood or saliva samples. As part of the FaceBase Biorepository, we are requesting families to submit biological samples from specific family members as well as information from other family members that might be affected with either the same condition or a similar condition. The medical and family history information that is collected includes other relevant information such as exposure to possible environmental causes during pregnancy. The biorepository is managed by Nichole Nidey, a research study coordinator, and Jeff Murray, a pediatric clinical geneticist and researcher. They are available to speak with family members regarding questions they may have, including providing information about the biorepository and making arrangements for the collection of samples for those who wish to participate. All participation is voluntary. Your name or other personally identifiable information (name, address, etc) will be removed before information is placed in the biorepository. Summary data to show how the database itself has been used overall as well as updates on whether specific findings might have been made using this database will be available on the FaceBase website at www.facebase.org. A newsletter containing this information will also be given to families and referring clinicians so that they may discuss the specifics with the families if there appears to be information that might be relevant in a particular case. Families will also need to sign a consent form that has been approved by the Institutional Review Board at the University of Iowa. Also, any submitted samples or data can also be removed from the database at any time should the family no longer wish to participate. Investigators interested in requesting DNA samples or for more information, please contact cleftresearch (at) uiowa.edu, Nichole Nidey, nichole-nidey (at) uiowa.edu or (319) 353-4365, or Jeff Murray, jeff-murray (at) uiowa.edu. | birth defect, genetic, environment, gene |
is listed by: One Mind Biospecimen Bank Listing has parent organization: FaceBase |
Cleft lip, Cleft palate, Family member, Campomelic Dysplasia, Chromosome Abnormality, Congenital Heart Disease, Facial clefting-Tessier Type 4, Gordon Syndrome, Hemifacial Microsomia, Idiopathic Short Stature, Marshall/Stickler, Microtia, Multiple Congenital Anomaly, Neurofibromatosis, Pierre Robin, Popliteal Pterygium Syndrome, Robinow, Downs syndrome, Townes-Brock Syndrome, Van der Woude Syndrome, Popliteal Pterygium Syndrome, Wildervanck Syndrome | THIS RESOURCE IS NO LONGER IN SERVICE | nlx_151379 | SCR_006001 | 2026-08-13 09:27:34 | 1 | |||||||
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PIPE-CLIP Resource Report Resource Website 10+ mentions |
PIPE-CLIP (RRID:SCR_005820) | PIPE-CLIP | production service resource, data analysis service, service resource, analysis service resource | A Galaxy framework-based online pipeline for reliable analysis of data generated by three types of CLIP-seq protocols: HITS-CLIP, PAR-CLIP and iCLIP. It provides both data processing and statistical analysis to determine candidate cross-linking regions, which are comparable to those regions identified from the original studies or using existing computational tools., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. | clip-seq, python, bioinformatics, r, high-thoughput sequencing, rna-binding protein, rna |
is listed by: OMICtools is related to: Galaxy has parent organization: University of Texas Southwestern Medical Center; Texas; USA has parent organization: Google Code |
PMID:24451213 | THIS RESOURCE IS NO LONGER IN SERVICE | OMICS_02254 | https://github.com/QBRC/PIPE-CLIP | SCR_005820 | PIPE-CLIP: a comprehensive online tool for CLIP-seq data analysis | 2026-08-13 09:27:22 | 10 | |||||
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Expression Profiler Resource Report Resource Website 1+ mentions |
Expression Profiler (RRID:SCR_005821) | Expression Profiler | production service resource, data analysis service, service resource, analysis service resource | THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice. | other analysis, cluster, analysis, visualization, gene expression, genomic, gene ontology, gene association, microarray, protein-protein interaction, gene, bio.tools |
is listed by: Gene Ontology Tools is listed by: Debian is listed by: bio.tools is related to: Gene Ontology has parent organization: European Bioinformatics Institute |
European Union ; Wellcome Trust ; Estonian Science Foundation 5724; Estonian Science Foundation 5722 |
PMID:15215431 | THIS RESOURCE IS NO LONGER IN SERVICE | biotools:expression_profiler, nlx_149323 | https://bio.tools/expression_profiler | SCR_005821 | Expression Profiler at the EBI | 2026-08-13 09:27:19 | 6 | ||||
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The Loom Resource Report Resource Website 1+ mentions |
The Loom (RRID:SCR_006877) | Loom | data or information resource, blog, narrative resource | The Loom is a blog about life, past and future. Written by DISCOVER contributing editor and columnist Carl Zimmer. Carl Zimmer writes about science regularly for the New York Times and magazines such as Discover, where he is a contributing editor and columnist. | has parent organization: Discover Magazine | nlx_83062 | SCR_006877 | 2026-08-13 09:27:39 | 1 | ||||||||||
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GOChase Resource Report Resource Website 1+ mentions |
GOChase (RRID:SCR_005822) | GOChase | production service resource, data analysis service, service resource, analysis service resource | GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations. # GOChase-History resolves the whole modification history of GO IDs. # GOChase-Correct highlights merged GO IDs and redirects to the correct primary term into which the secondary ID was merged. For obsolete GO terms, the nearest non-discarded parent term is recommended by GOChase. This function may be used by GO browsers such as AmiGO and QuickGO to fix broken hyperlinks. # A whole database (such as LocusLink) as a flat file can be loaded into GOChase, reporting the annotation errors and GOChase corrections. # When one inputs a GO ID, GOChase will resolve all gene products annotated with the GO ID across all the major databases. Platform: Online tool | other analysis, historical views of go, gene ontology, annotation |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: Seoul National University College of Medicine; Seoul; South Korea |
Ministry of Health and Welfare - Republic of Korea 0405-BC0206040004 | PMID:15513987 | Free for academic use | nlx_149324 | SCR_005822 | GOChase: correcting errors from gene ontology-based annotations for gene products | 2026-08-13 09:27:33 | 1 | |||||
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Sapienta Resource Report Resource Website 1+ mentions |
Sapienta (RRID:SCR_006993) | SAPIENTA | software resource, source code, software application | Software to help researchers process scientific papers faster and get the information they are interested in out of them. This is achieved by automating the recognition of core scientific concepts such as Motivation, Method, Result, Conclusion in papers and uses them to generate automatic summaries. This SAPIENTA tool adds additional functionality to the SAPIENT tool, an annotation tool implemented as a web application which enables experts to annotate scientific papers, sentence by sentence manually, according to the Core Scientific Concept (CSC) schema. | semantic mark up, semantic, annotation, annotation software | is listed by: FORCE11 | JISC | nlx_151311 | SCR_006993 | SAPIENTA - Automating the Semantic Annotation of Papers, Semantic Annotation of Papers: Interface & ENrichment Tool Automated | 2026-08-13 09:27:43 | 1 | |||||||
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MCMBB Resource Report Resource Website 1+ mentions |
MCMBB (RRID:SCR_006198) | MCMBB | production service resource, data analysis service, service resource, analysis service resource | A web tool used in the discrimination of beta-barrel outer membrane proteins with a Markov chain model. MCMBB is a fast algorithm, which discriminates beta-barrel outer membrane proteins from globular proteins and from alpha-helical membrane proteins. The algorithm is based on a 1st order Markov Chain model, which captures the alternating pattern of hydrophilic-hydrophobic residues occurring in the membrane-spanning beta-strands of beta-barrel outer membrane proteins. The model achieves high accuracy in discriminating outer membrane proteins, since it can discriminate beta-barrel outer membrane with a correct classification rate of 90.08% and the globular proteins with a correct classification rate of 92.67%. When submitting alpha-helical membrane proteins, the method shows an accuracy of 100%. A score greater than zero, indicates that the protein is more likely to be a beta-barrel outer membrane protein, whereas a result lower than zero, indicates that the protein is probable not a beta-barrel. You may enter up to 1000 sequences in Fasta format. | algorithm, beta-barrel outer membrane protein, globular protein, alpha-helical membrane protein, markov chain model, beta-barrel, protein, outer membrane protein, classification, fasta, model |
is listed by: 3DVC has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
Acknowledgement requested | nlx_151742 | SCR_006198 | MCMBB: Markov Chain Model for Beta Barrels | 2026-08-13 09:27:25 | 2 | |||||||
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waveTM Resource Report Resource Website 1+ mentions |
waveTM (RRID:SCR_006199) | waveTM | production service resource, data analysis service, service resource, analysis service resource | A web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. A sliding window of 20 residues is used in order to calculate an average residue hydrophobicity profile, using a hydrophobicity scale. Discrete Wavelet Transform is applied on the average residue hydrophobicity signal and the different frequency coefficients produced are adaptively thresholded so that a denoised signal is reconstructed. A dynamic programming algorithm processes the denoised signal to provide the optimal model for the number, the length and the location of membrane-spanning segments. The end points of the predicted segments are extended to include flanking hydrophobic residues. Topology prediction can also be obtained in conjunction with OrienTM (Liakopoulos et al, 2001). Analysis of a non-redundant test set, provides a ~95% per segment accuracy and ~90% per residue accuracy. Now, you can: * Run waveTM on a sequence * Browse the results obtained with the algorithm * View additional material concerning the hydrophobicity scale | wavelet, predict, transmembrane segment, alpha-helical membrane protein, protein, protein sequence, discrete wavelet transform, sequence, hydrophobicity scale, hydrophobicity, transmembrane protein, topology, transmembrane |
is related to: orienTM is related to: PRED-TMR has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
University of Athens; Athens; Greece | PMID:15107018 | Freely available | nlx_151743 | SCR_006199 | waveTM: Wavelet-based transmembrane segment prediction | 2026-08-13 09:27:36 | 3 | |||||
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PRED-COUPLE 2 Resource Report Resource Website 1+ mentions |
PRED-COUPLE 2 (RRID:SCR_006193) | PRED-COUPLE 2 | production service resource, data analysis service, service resource, analysis service resource | A tool that predicts the coupling specificity of G-protein coupled receptors to G-proteins. We present a method that combines hidden Markov models and a feed-forward artificial neural network to overcome these limitations, while producing the most accurate predictions currently available. Using an up-to-date curated dataset, our method yields a 94% correct classification rate in a 5-fold cross-validation test. The method predicts also promiscuous coupling preferences, including coupling to G12/13, whereas unlike other methods avoids overpredictions (false positives) when non-GPCR sequences are encountered. * The PRED-COUPLE 2.00 system predicts coupling specificty of GPCRs to all families of G-proteins (including G12/13). * Coupling to more than one G-protein families can also be predicted with this tool. * No membrane topology information is required. Furthermore, no membrane topology prediction is executed by this method. * The method is based on a refined library of highly-discriminative Hidden Markov Models. Hits from individual profiles are combined by a feed-forward Artificial Neural Network to produce the final output. * Seven (7) transmembrane receptor signatures from the Pfam database version 17.00 are also applied in order to verify a true GPCR sequence. When a query sequence is not recognized as a 7 transmembrane receptor a message is shown. | predict, g-protein coupled receptor, g-protein, fasta, hidden markov model, coupling specificity | has parent organization: University of Athens Biophysics and Bioinformatics Laboratory | Greek Ministry of National Education and Religious Affairs | PMID:16174684 PMID:15847681 |
Free for academic use | nlx_151738 | SCR_006193 | PRED-COUPLE | 2026-08-13 09:27:25 | 6 | |||||
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PRED-TMBB Resource Report Resource Website 50+ mentions |
PRED-TMBB (RRID:SCR_006190) | PRED-TMBB | production service resource, data analysis service, service resource, analysis service resource | A web tool, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the gram-negative bacteria outer membrane proteins, and of discriminating such proteins from water-soluble ones when screening large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of the correct prediction rather than the likelihood of the sequences. The training is performed on a non-redundant database consisting of 16 outer membrane proteins (OMP''s) with their structures known at atomic resolution. We show that we can achieve predictions at least as good comparing with other existing methods, using as input only the amino-acid sequence, without the need of evolutionary information included in multiple alignments. The method is also powerful when used for discrimination purposes, as it can discriminate with a high accuracy the outer membrane proteins from water soluble in large datasets, making it a quite reliable solution for screening entire genomes. This web-server can help you run a discriminating process on any amino-acid sequence and thereafter localize the transmembrane strands and find the topology of the loops. | protein, hidden markov model, prediction, membrane protein, beta-barrel outer membrane protein, gram-negative bacteria, topology, outer membrane protein, beta-barrel protein, probability, transmembrane strand, bio.tools, FASEB list |
is listed by: bio.tools is listed by: Debian has parent organization: University of Athens Biophysics and Bioinformatics Laboratory |
Greek Ministry of National Education and Religious Affairs | PMID:15215419 PMID:15070403 |
Acknowledgement requested | biotools:pred-tmbb, nlx_151734 | https://bio.tools/pred-tmbb | SCR_006190 | PRED-TMBB: A Hidden Markov Model method capable of predicting and discriminating beta-barrel outer membrane proteins | 2026-08-13 09:27:26 | 58 | ||||
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UCSD-Nature Signaling Gateway Molecule Pages Resource Report Resource Website 10+ mentions |
UCSD-Nature Signaling Gateway Molecule Pages (RRID:SCR_006907) | SGMP | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Relational database of all significant published qualitative and quantitative information on cell signaling proteins. The Molecule Pages database was developed with the specific aim of allowing interactions, and indeed whole pathways, to be modeled. The goal is to filter the data to present only validated information. In addition, the Gateway is the home of Signaling Update, which provides a one-stop overview of the latest and hottest research in cell signaling for both the specialist and non-specialist alike. | database, data model, cell signaling pathway, molecule, protein, signal transduction |
is listed by: 3DVC has parent organization: University of California at San Diego; California; USA |
Genentech Inc ; National Institute of General Medical Sciences |
PMID:21505029 PMID:17965093 PMID:12478304 |
THIS RESOURCE IS NO LONGER IN SERVICE | r3d100011690, nif-0000-03604, SCR_013230, nif-0000-20810 | https://doi.org/10.17616/R3V343 | SCR_006907 | Molecule Pages: A comprehensive signaling database, UCSD - Signaling Gateway Molecule Pages, Alliance for Cellular Signaling Molecule Pages Database | 2026-08-13 09:27:36 | 13 | ||||
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GO-Module Resource Report Resource Website 1+ mentions |
GO-Module (RRID:SCR_005813) | GO-Module | production service resource, data analysis service, service resource, analysis service resource | GO-Module provides an interface to reduce the dimensionality of GO enrichment results and produce interpretable biomodules of significant GO terms organized by hierarchical knowledge that contain only true positive results. Users can download a text file of GO terms annotated with their significance and identified biomodules, a network visualization of resultant GO IDs or terms in PDF format, and view results in an online table. Platform: Online tool | functional similarity, visualization, other analysis, reduce the dimensionality of go enrichment results, produce interpretable biomodules of significant go terms, gene ontology, ontology or annotation visualization, annotation |
is listed by: Gene Ontology Tools is related to: Gene Ontology is related to: AmiGO has parent organization: University of Illinois at Chicago; Illinois; USA |
NIH ; Cancer Research Foundation ; NLM K22 LM008308; NCI 1U54CA121852; NCRR UL1 RR024999 |
PMID:21421553 | Free for academic use | nlx_149322 | SCR_005813 | Hierarchical optimization of enriched GO terms | 2026-08-13 09:27:22 | 3 | |||||
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Pythonxy Resource Report Resource Website 10+ mentions |
Pythonxy (RRID:SCR_006903) | Python-xy, Python(x, y) | software development tool, software resource, source code, software application | Scientific and engineering development software for numerical computations, data analysis and data visualization based on Python programming language, Qt graphical user interfaces and Spyder interactive scientific development environment. Used to interpreted languages (such as MATLAB or IDL) or compiled languages (C/C++ or Fortran) to switch to Python. | program, language, python, computation, data analysis, data visualization, plugin | is related to: Spyder | Free, Available for download, Freely available | nlx_149232 | http://www.pythonxy.com, https://code.google.com/p/pythonxy/wiki/Welcome | SCR_006903 | pythonxy - Scientific-oriented Python Distribution based on Qt and Spyder, Python(x, y) - Scientific oriented Python Distribution based on Qt and Spyder | 2026-08-13 09:27:39 | 10 | ||||||
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GeneTerm Linker Resource Report Resource Website 1+ mentions |
GeneTerm Linker (RRID:SCR_006385) | GTLinker | production service resource, data analysis service, service resource, analysis service resource | Web application that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. It can also be accessed through its web service. | gene, functional annotation, function, functional metagroup, p-value, annotation, web service |
is listed by: OMICtools is related to: Gene Ontology is related to: KEGG is related to: InterPro has parent organization: Spanish National Research Council; Madrid; Spain |
PMID:21949701 | Acknowledgement requested | OMICS_02227 | SCR_006385 | GeneTerm Linker - post enrichment functional association by non-redundant reciprocal linkage | 2026-08-13 09:27:37 | 2 | ||||||
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mitopred Resource Report Resource Website 1+ mentions |
mitopred (RRID:SCR_006135) | MITOPRED | production service resource, data analysis service, service resource, analysis service resource | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution. | yeast, c. elegans, drosophila, mouse, human, arabidopsis, bio.tools |
is listed by: Debian is listed by: bio.tools is listed by: SoftCite has parent organization: University at Albany; New York; USA |
THIS RESOURCE IS NO LONGER IN SERVICE | biotools:mitopred, nif-0000-03956, BioTools:mitopred | https://bio.tools/mitopred, https://bio.tools/mitopred, https://bio.tools/mitopred | SCR_006135 | A genome-scale method for predicting mitochondrial proteins | 2026-08-13 09:27:24 | 7 | ||||||
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Genotype-IBD Sharing Test Resource Report Resource Website 100+ mentions |
Genotype-IBD Sharing Test (RRID:SCR_006257) | GIST | software resource, resource, software application | Software package to test if a marker can account in part for the linkage signal in its region. There are two versions of the software: Windows and Linux/Unix. | identical by descent, genotype, gene, genetic, genomic, unix, ms-windows, linux, linkage disequilibrium, linkage, association |
is listed by: Genetic Analysis Software has parent organization: Vanderbilt University; Tennessee; USA |
Vanderbilt Diabetes Center ; NHGRI HG00376; NIDDK DK62370; NHGRI N01-HG-15465 |
PMID:14872409 | nlx_154133 | http://phg.mc.vanderbilt.edu/content/gist | SCR_006257 | 2026-08-13 09:27:36 | 120 | ||||||
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MEDIE Resource Report Resource Website 1+ mentions |
MEDIE (RRID:SCR_006254) | MEDIE | production service resource, data analysis service, service resource, analysis service resource | An intelligent search engine to retrieve biomedical correlations from MEDLINE, based on indexing by Natural Language Processing and Text Mining techniques. You can find abstracts/sentences in MEDLINE by specifying semantics of correlations; for example, What activates p53 and What causes colon cancer. Semantic search uses a semantic query for finding biomedical correlations. Input a subject, a verb, and an object of a concept (or either of them) into a form. Results of the query will be shown in a second. (E.g., What does p53 activate? (subject=p53, verb=activate)) Reference: Miyao, Yusuke, Tomoko Ohta, Katsuya Masuda, Yoshimasa Tsuruoka, Kazuhiro Yoshida, Takashi Ninomiya and Jun''''ichi Tsujii (2006) Semantic Retrieval for the Accurate Identification of Relational Concepts in Massive Textbases. Proceedings COLING-ACL 2006. Sydney, Australia, pp. 1017--1024. | natural language processing, text mining, semantic search, computational linguistics, search engine |
is used by: BioLexicon is listed by: OMICtools is listed by: FORCE11 is related to: MEDLINE has parent organization: University of Tokyo; Tokyo; Japan has parent organization: National Centre for Text Mining |
nif-0000-06682, OMICS_01188 | http://www-tsujii.is.s.u-tokyo.ac.jp/medie/, https://www.force11.org/node/4643 | SCR_006254 | 2026-08-13 09:27:27 | 3 |
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