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NameTDescription# Ann.AuthorMaintainer Updated_atStatus

481-500 / 593 show all
Test_Project 0Ingenerfingenerf2023-11-29Testing
PGDBj_disease_curation1 disease curation test348ichihara_hisakoichihara_hisako2023-12-03Testing
simple1 4.34 Khxr-2016_dlut2023-11-29
OryzaGP1 A dataset for Named Entity Recognition for rice gene0Huy Do. Pierre Larmande2019-01-31Uploading
Testing Testing241Hyun-Seok Parkhsp202023-11-28Testing
week10 57hsp202023-11-28
youworks-test this is test annotation.0Hisato Terada2023-11-29Testing
traitCurationTest_ichihara testProject1508064ichihara_hisakoHisako Ichihara2023-11-29Testing
ichiharatest_150825_3 test0ichihara_hisakoHisako Ichihara2023-11-26Testing
ichiharatest_150825_2 test0ichihara_hisakoHisako Ichihara2015-09-11Testing
ichiharatest_150825 test0ichihara_hisakoHisako Ichihara2023-11-29Testing
ichiharatest_150830_1 test99Hisako Ichihara2023-11-29Testing
falsetest_150825 test0ichihara_hisakoHisako Ichihara2015-09-11Testing
Fragaria_ananassa_genes 0hidekih152023-11-28
RELASIGEBLAH7hhaider5 277hhaider52023-11-29Developing
OGERtesthhaider5 465hhaider52023-11-29
pubmed_test 02023-11-29
Virus300 300 abstracts from virology journals annotated with viral proteins and species0http://aclweb.org/anthology/W/W17/W17-2311.pdfhelencook2017-08-07Released
proj_h_1 6.7 K2023-11-24
CoMAGC In order to access the large amount of information in biomedical literature about genes implicated in various cancers both efficiently and accurately, the aid of text mining (TM) systems is invaluable. Current TM systems do target either gene-cancer relations or biological processes involving genes and cancers, but the former type produces information not comprehensive enough to explain how a gene affects a cancer, and the latter does not provide a concise summary of gene-cancer relations. In order to support the development of TM systems that are specifically targeting gene-cancer relations but are still able to capture complex information in biomedical sentences, we publish CoMAGC, a corpus with multi- faceted annotations of gene-cancer relations. In CoMAGC, a piece of annotation is composed of four semantically orthogonal concepts that together express 1) how a gene changes, 2) how a cancer changes and 3) the causality between the gene and the cancer. The multi-faceted annotations are shown to have high inter-annotator agreement. In addition, the annotations in CoMAGC allow us to infer the prospective roles of genes in cancers and to classify the genes into three classes according to the inferred roles. We encode the mapping between multi-faceted annotations and gene classes into 10 inference rules. The inference rules produce results with high accuracy as measured against human annotations. CoMAGC consists of 821 sentences on prostate, breast and ovarian cancers. Currently, the corpus deals with changes in gene expression levels among other types of gene changes.1.53 KLee et alHee-Jin Lee2023-11-24Released
NameT# Ann.AuthorMaintainer Updated_atStatus

481-500 / 593 show all
Test_Project 0Ingenerfingenerf2023-11-29Testing
PGDBj_disease_curation1 348ichihara_hisakoichihara_hisako2023-12-03Testing
simple1 4.34 Khxr-2016_dlut2023-11-29
OryzaGP1 0Huy Do. Pierre Larmande2019-01-31Uploading
Testing 241Hyun-Seok Parkhsp202023-11-28Testing
week10 57hsp202023-11-28
youworks-test 0Hisato Terada2023-11-29Testing
traitCurationTest_ichihara 4ichihara_hisakoHisako Ichihara2023-11-29Testing
ichiharatest_150825_3 0ichihara_hisakoHisako Ichihara2023-11-26Testing
ichiharatest_150825_2 0ichihara_hisakoHisako Ichihara2015-09-11Testing
ichiharatest_150825 0ichihara_hisakoHisako Ichihara2023-11-29Testing
ichiharatest_150830_1 99Hisako Ichihara2023-11-29Testing
falsetest_150825 0ichihara_hisakoHisako Ichihara2015-09-11Testing
Fragaria_ananassa_genes 0hidekih152023-11-28
RELASIGEBLAH7hhaider5 277hhaider52023-11-29Developing
OGERtesthhaider5 465hhaider52023-11-29
pubmed_test 02023-11-29
Virus300 0http://aclweb.org/anthology/W/W17/W17-2311.pdfhelencook2017-08-07Released
proj_h_1 6.7 K2023-11-24
CoMAGC 1.53 KLee et alHee-Jin Lee2023-11-24Released