Staphylococcus | | | 7.46 K | haruo | haruo | 2023-11-29 | Testing | |
Tester | | Test for cancer | 93 | Han | | 2023-11-30 | Testing | |
hahm_test | | hahm_test | 0 | hahm | kaist_nlp | 2019-04-02 | Testing | |
LocText | | The manually annotated corpus consists of 100 PubMed abstracts annotated for proteins, subcellular localizations, organisms and relations between them. The focus of the corpus is on annotation of proteins and their subcellular localizations. | 2.29 K | Goldberg et al | Shrikant Vinchurkar | 2023-11-29 | Released | |
GENIAcorpus | | multi_cell (1,782)
mono_cell (222)
virus (2,136)
protein_family_or_group (8,002)
protein_complex (2,394)
protein_molecule (21,290)
protein_subunit (942)
protein_substructure (129)
protein_domain_or_region (1,044)
protein_other (97)
peptide (521)
amino_acid_monomer (784)
DNA_family_or_group (332)
DNA_molecule (664)
DNA_substructure (2)
DNA_domain_or_region (39)
DNA_other (16)
RNA_family_or_group (1,545)
RNA_molecule (554)
RNA_substructure (106)
RNA_domain_or_region (8,237)
RNA_other (48)
polynucleotide (259)
nucleotide (243)
lipid (2,375)
carbohydrate (99)
other_organic_compound (4,113)
body_part (461)
tissue (706)
cell_type (7,473)
cell_component (679)
cell_line (4,129)
other_artificial_source (211)
inorganic (258)
atom (342)
other (21,056)
| 78.9 K | GENIA Project | Yue Wang | 2023-11-29 | Released | |
pubmed-sentences-benchmark | | A benchmark data for text segmentation into sentences.
The source of annotation is the GENIA treebank v1.0.
Following is the process taken.
began with the GENIA treebank v1.0.
sentence annotations were extracted and converted to PubAnnotation JSON.
uploaded. 12 abstracts met alignment failure.
among the 12 failure cases, 4 had a dot('.') character where there should be colon (':'). They were manually fixed then successfully uploaded: 7903907, 8053950, 8508358, 9415639.
among the 12 failed abstracts, 8 were "250 word truncation" cases. They were manually fixed and successfully uploaded. During the fixing, manual annotations were added for the missing pieces of text.
30 abstracts had extra text in the end, indicating copyright statement, e.g., "Copyright 1998 Academic Press." They were annotated as a sentence in GTB. However, the text did not exist anymore in PubMed. Therefore, the extra texts were removed, together with the sentence annotation to them.
| 18.4 K | GENIA project | Jin-Dong Kim | 2023-11-28 | Released | |
jnlpba-st-training | | The training data used in the task came from the GENIA version 3.02 corpus, This was formed from a controlled search on MEDLINE using the MeSH terms "human", "blood cells" and "transcription factors". From this search, 1,999 abstracts were selected and hand annotated according to a small taxonomy of 48 classes based on a chemical classification. Among the classes, 36 terminal classes were used to annotate the GENIA corpus. For the shared task only the classes protein, DNA, RNA, cell line and cell type were used. The first three incorporate several subclasses from the original taxonomy while the last two are interesting in order to make the task realistic for post-processing by a potential template filling application. The publication year of the training set ranges over 1990~1999. | 51.1 K | GENIA | Yue Wang | 2023-11-26 | Released | |
bionlp-st-epi-2011-training | | The training dataset from the Epigenetics and Post-translational Modifications (EPI) task in the BioNLP Shared Task 2011.
The core entities of the task are genes and gene products (RNA and proteins), identified in the data simply as "Protein" annotations. | 7.59 K | GENIA | Yue Wang | 2023-11-29 | Released | |
LitCovid-OGER | | Using OGER (http://www.ontogene.org/resources/oger) to detect entities from 10 different vocabularies | 9.31 K | Fabio Rinaldi | Nico Colic | 2023-11-29 | Released | |
2015-BEL-Sample-2 | | The 295 BEL statements for sample set used for the 2015 BioCreative challenge. | 11.4 K | Fabio Rinaldi | Nico Colic | 2023-11-28 | Released | |
LitCovid-OGER-BB | | Using OGER (www.ontogene.com) and Biobert to obtain annotations for 10 different vocabularies. | 308 K | Fabio Rinaldi | Nico Colic | 2023-11-28 | Released | |
LitCovid-PMC-OGER-BB | | Annotating PMC articles with OGER and BioBert, according to an hand-crafted Covid-specific dictionary and the 10 different CRAFT ontologies (http://bionlp-corpora.sourceforge.net/CRAFT/):
Chemical Entities of Biological Interest (CHEBI),
Cell Ontology (CL),
Entrez Gene (UBERON),
Gene Ontology (biological process (GO-BP), cellular component (GO-CC), and molecular function (GO-MF),
NCBI Taxonomy (NCBITaxon),
Protein Ontology (PR),
Sequence Ontology (SO) | 3.14 M | Fabio Rinaldi | Nico Colic | 2023-11-24 | Developing | |
2015-BEL-Sample | | An attempt to upload 295 BEL statements, i.e. the sample set used for the 2015 BioCreative challenge.
| 58 | Fabio Rinaldi | Fabio Rinaldi | 2023-11-29 | Testing | |
SPECIES800 | | SPECIES 800 (S800): an abstract-based manually annotated corpus. S800 comprises 800 PubMed abstracts in which organism mentions were identified and mapped to the corresponding NCBI Taxonomy identifiers.
Described in:
The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text.
Pafilis E, Frankild SP, Fanini L, Faulwetter S, Pavloudi C, et al. (2013). PLoS ONE, 2013, 8(6): e65390. doi:10.1371/journal.pone.0065390 | 3.71 K | Evangelos Pafilis, Sune P. Frankild, Lucia Fanini, Sarah Faulwetter, Christina Pavloudi, Aikaterini Vasileiadou, Christos Arvanitidis, Lars Juhl Jensen | evangelos | 2023-11-28 | Released | |
SPECIES800_autotagged | | This project comprises the SPECIES800 corpus documents automatically annotated by the Jensenlab tagger.
Annotated entity types are:
Genes/proteins from the mentioned organisms (and any human ones)
PubChem Compound identifiers
NCBI Taxonomy entries
Gene Ontology cellular component terms
BRENDA Tissue Ontology terms
Disease Ontology terms
Environment Ontology terms
The SPECIES 800 (S800) comprises 800 PubMed abstracts. In its original form species mentions were manually identified and mapped to the corresponding NCBI Taxonomy identifiers.
Described in:
The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text.
Pafilis E, Frankild SP, Fanini L, Faulwetter S, Pavloudi C, et al. (2013). PLoS ONE, 2013, 8(6): e65390. doi:10.1371/journal.pone.0065390.
The manually annotated corpus is also available as a PubAnnotation project (see here).
| 0 | Evangelos Pafilis, Sampo Pyysalo, Lars Juhl Jensen | evangelos | 2015-11-20 | Testing | |
Erin_test | | @ Yonsei University | 0 | Erin | ErinHJ_Kim | 2023-11-29 | Testing | |
pubmed-enju-pas | | Annotating PubMed abstracts for predicate-argument structure (PAS). Enju 2.4.2 is used to automatically compute PAS. | 19.1 M | Enju | Jin-Dong Kim | 2023-11-24 | Developing | |
ENG_RE | | Entities and relations annotations from the following ontologies: Disease Ontology ('DO'), Gene Ontology ('GO'), Human Phenotype Ontology ('HPO'), and ChEBI ontology ('CHEBI'). | 224 | Diana Sousa | dpavot | 2023-11-29 | Developing | |
PGR-UNK | | Identification of Unknown Relations
| 91 | Diana Sousa | dpavot | 2023-11-29 | Developing | |
PGR-FAL | | Identification of False Relations | 128 | Diana Sousa | dpavot | 2023-11-29 | Developing | |