dataesr/scientific-paragraphs-categorization huggingface dataset:
The IMGT ® IG and TR gene names  [3] [4] [5] [6]  were approved by the Human Genome Organisation (HUGO) Nomenclature Committee (HGNC) in 1999  [88, 89]  and were endorsed by the WHO-IUIS Nomenclature Subcommittee for IG and TR  [46, 47]. The IMGT ® IG and TR gene names are the official international reference and, as such, have been entered in IMGT/GENE-DB  [8] , in the Genome Database (GDB)  [90] , in LocusLink at the National Center for Biotechnology Information (NCBI) USA  [91] , in Entrez Gene (NCBI) when this database (now designated as "Gene") superseded LocusLink  [92] , in NCBI MapViewer, in Ensembl at the European Bioinformatics Institute (EBI)  [93] , and in the Vertebrate Genome Annotation (Vega) Browser  [94]  at the Wellcome Trust Sanger Institute (UK). HGNC, Gene NCBI, Ensembl, and Vega have direct links to IMGT/GENE-DB  [8].
The IMGT/Collier-de-Perles tool is integrated in IMGT/DomainGapAlign  [10, 25, 26]  (analysis of user IG amino acid sequences containing V and/or C domains) and in IMGT/V-QUEST  [13] [14] [15] [16] [17] [18]  (analysis of user nucleotide sequences containing V domains) (Table  5 ). IMGT Colliers de Perles for V and C domains are provided in IMGT/2Dstructure-DB (for amino acid sequences in the database) and in IMGT/3Dstructure-DB (on two layers with hydrogen bonds for the V or C domains, for 3D structures in the database)  [9] [10] [11]  (Table  5 ). -Applications: somatic mutations in chronic lymphocytic leukemia (CLL) prognostic IMGT/HighV-QUEST  [22] [23] [24]  1. Introduction of IMGT gaps 2. Identification of indels and their correction  [17]  (by default). 3. Identification of the closest V, D and J genes and alleles 4.
The functionalities of IMGT/HighV-QUEST include: the introduction of IMGT gaps; the identification of indels and their correction  [17]  (by default); the identification of the closest V, D, and J genes and alleles; the IMGT/JunctionAnalysis results; the description of mutations and amino acid changes; the annotation by IMGT/Automat; the NGS statistical analysis; and the characterization of the IMGT clonotypes (AA)  [23, 24, 70]  (Table  5 ). As for the other IMGT ® databases and tools, IMGT/HighV-QUEST is freely available for academics. However, the IMGT/HighV-QUEST Welcome page requires user identification and provides, for new users, a link to register. User identification has been set to avoid nonrelevant use and overload of the server, and to contact the user if needed. The user identification gives access to the IMGT/HighV-QUEST Search page.
For identifying "IMGT clonotypes (AA)" in a given IMGT/HighV-QUEST dataset, the "1 copy" are filtered to select for sequences with in-frame junction, conserved anchors 104 and 118 ("C" is 2nd-CYS 104, and "F" or "W' is the J-PHE or J-TRP 118) and for V and J functional or ORF, and "single allele" (for V and J)  [24]. By essence, an "IMGT clonotype (AA)" is "unique" for a given dataset. For that reason, each "IMGT clonotype (AA)", in a given dataset, has a unique set identifier and, importantly, has a unique representative sequence selected by IMGT/HighV-QUEST among the "1 copy" "single allele" (for V and J), based on the highest percent of identity of the V-REGION ("V %") compared to that of the closest germline, and/or on the sequence length (thus the most complete V-REGION)  [24, 70].
The IMGT/DomainSeq reference directory comprises AA sequences of domains, or of core regions for V and J, of functional (F), ORF (open reading frame) and in frame pseudogene (P) genes. As IMGT ® alleles are characterized at the nucleotide level, identical sequences at the amino acid level may therefore correspond to different alleles, in the IMGT/DomainSeq reference directory. The sequences can be displayed by querying IMGT/DomainDisplay  [1]. IMGT/3Dstructure-DB  [9] [10] [11] ; the IMGT ® structure database; provides IMGT ® annotation and contact analysis of IG 3D structures; and paratope/epitope description of IG/antigen complexes (Table  5 ). There is one "IMGT/3Dstructure-DB card" per IMGT/3Dstructure-DB entry and this card provides access to all data related to that entry. The "PDB code" (4 letters and/or numbers; e.
g. , 1n0x) is used as "IMGT entry ID" for the 3D structures obtained from the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB)  [98]. The IMGT/3Dstructure-DB card provides eight search/display options: "Chain details"; "Contact analysis"; "Paratope and epitope"; "3D visualization 4. 1. 4. Paratope and Epitope In an IG/Ag complex, the amino acids in contact at the interface between the IG and the Ag constitute the paratope on the IG V-DOMAIN surface and the epitope on the Ag surface. For IG/Ag, the paratope and epitope are displayed in Contact analysis (Figure  5B, C ), but for each V domain separately. Clicking on the "Paratope and epitope" tag (displayed in the IMGT/3Dstructure-DB card, only if relevant), gives access to "IMGT paratope and epitope details", which are described in a standardized way.
Each amino acid which belongs to the paratope is defined by its position in an IG V-DOMAIN. Each amino acid that belongs to the epitope is defined by its position in the chain in the 3D structure or, if the antigen belongs to an IgSF or MhSF protein and if the epitope is part of a characterized V, C, or G domain, by its position in the domain according to the IMGT unique numbering. The "IMGT/3Dstructure-DB card" is available for each entry of the database. The "Chain details" shows, first, information on the chain (Chain ID, Chain length, IMGT chain description, Chain sequence), then a detailed description of each domain of the chain. The description of the V-DOMAIN (VH) and C-DOMAIN (CH1) of the VH-CH1 chain (1n0x_H) of the b12 Fab is shown. A similar result display interface is provided in IMGT/2Dstructure-DB cards but without "Contact analysis" (and without hydrogen bonds in IMGT Collier de Perles on 2 layers); (B) IMGT/3Dstructure-DB Domain pair contacts between the "VH" and the "Ligand" (antigen, Ag) of an IG/Ag complex.
IMGT/2Dstructure-DB IMGT/2Dstructure-DB was created as an extension of IMGT/3Dstructure-DB  [9] [10] [11]  to describe and analyze amino acid sequences of chains and domains for which no 3D structures were available (Table  5 ). IMGT/2Dstructure-DB uses the IMGT/3Dstructure-DB informatics frame and interface, which allow one to analyze, manage and query IG (and also TR and MH, as well as other IgSF and MhSF) and engineered proteins (FPIA, CPCA) as polymeric receptors made of several chains, in contrast to the IMGT/LIGM-DB sequence database that analyzes and manages sequences individually  [7]. The amino acid sequences are analysed with the IMGT ® criteria of standardized identification  [57] , description  [58] , nomenclature  [59]  and numerotation  [60] [61] [62] [63] [64] [65]. The current IMGT/2Dstructure-DB entries include amino acid sequences of antibodies from Kabat  [95]  (those for which there were no available nucleotide sequences) and amino acid sequences of mAb and FPIA from the WHO-INN programme  [12, 48, 49].
Figure5. IMGT/3Dstructure-DB. (A) IMGT/3Dstructure-DB card. The "IMGT/3Dstructure-DB card" is available for each entry of the database. The "Chain details" shows, first, information on the chain (Chain ID, Chain length, IMGT chain description, Chain sequence), then a detailed description of each domain of the chain. The description of the V-DOMAIN (VH) and C-DOMAIN (CH1) of the VH-CH1 chain (1n0x_H) of the b12 Fab is shown. A similar result display interface is provided in IMGT/2Dstructure-DB cards but without "Contact analysis" (and without hydrogen bonds in IMGT Collier de Perles on 2 layers); (B) IMGT/3Dstructure-DB Domain pair contacts between the "VH" and the "Ligand" (antigen, Ag) of an IG/Ag complex. The VH is from the VH-CH1 chain (1n0x_H) of the b12 Fab and the ligand is a synthetic peptide (1n0x_P).
Acknowledgments I am grateful to  Gérard Lefranc  and  Sophia Kossida  for helpful discussion,  Patrice Duroux ,  Véronique Giudicelli ,  Joumana Jabado-Michaloud  and  Géraldine Folch  for developing and managing the IMGT ® system,  Safa Aouinti ,  Pablo Baeza-Centurion ,  Pascal Bento ,  Emilie Carillon ,  Hugo Duvergey ,  Saïda Hadi-Saljoki ,  Amélie Houles ,  Arthur Lavoie ,  Typhaine Paysan-Lafosse ,  Marine Peralta ,  Souphatta Sasorith , for their expertise and constant motivation, and all the previous members of the  IMGT ® team , for their invaluable contribution. We thank  Cold Spring Harbor Protocol Press  for the pdf of the IMGT Booklet available in IMGT references. IMGT ® is a registered trademark of CNRS. IMGT ® is member of the  International Medical Informatics Association (IMIA).
IMGT ® was funded in part by the  BIOMED1  ( BIOCT930038 ), Biotechnology  BIOTECH2  ( BIO4CT960037 ), 5th  PCRDT Quality of Life and Management of Living Resources  ( QLG2-2000-01287 ), and 6th  PCRDT Information Science and Technology (ImmunoGrid ,  FP6 IST-028069 ) programmes of the  European Union (EU). IMGT ® is the thematic  ELIXIR Immunoinformatics node of the Institut Français de Bioinformatique IFB. IMGT ® is currently supported by the  Centre National de la Recherche Scientifique (CNRS) , the  Ministère de l'Enseignement Supérieur et de la Recherche (MESR) , the  Montpellier University , the  Agence Nationale de la Recherche (ANR)   Labex MabImprove  ( ANR-10-LABX-53-01 ),  BioCampus Montpellier , the  Région Languedoc-Roussillon (Grand Plateau Technique pour la Recherche (GPTR).
DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput sequencing require fast and effective methods for en masse species assignments. In this article, we focus on selecting and re-annotating a set of marker reference sequences that represent each currently accepted order of Fungi. The particular focus is on sequences from the internal transcribed spacer region in the nuclear ribosomal cistron, derived from type specimens and/or ex-type cultures. Reannotated and verified sequences were deposited in a curated public database at the National Center for Biotechnology Information (NCBI), namely the RefSeq Targeted Loci (RTL) database, and will be visible during routine sequence similarity searches with NR_prefixed accession numbers.
Improvements in how electronic data are disseminated also prompted changes in the ICN, namely, a requirement to register all new fungal taxonomic names at one or more online repositories. Recently, three candidates, Fungal Names, Index Fungorum or MycoBank were proposed  (4). These databases provide an invaluable source of important information on vouchers that facilitate fungal identification. This, in turn, will aid the large-scale reassessment of taxonomic names required as part of the transition to use one name for each fungal species  (5, 6). It will also improve the integration to a sequence-based classification  (7). For effective DNA-based identification to be implemented, the scientific community needs a continuously expanding, public and well-annotated set of DNA sequences. Each of these sequences needs to be associated with accurate specimen data and a current species name.
Current state of sequence databases GenBank, together with its collaborative partners in the International Nucleotide Sequence Databases Collaboration (INSDC), i. e. the DNA Data Bank of Japan and the European Nucleotide Archive (ENA) has long been the most comprehensive resource of nucleotide data  (8). It is tasked with archiving the world's genetic data as an open resource to all researchers. In spite of an extensive review of user submissions, GenBank essentially relies on users to accurately name their sequences. This results in a significant number of sequences deposited under erroneous or imprecise names, so-called 'dark taxa'  (9, 10). This complicates efforts to clearly assign taxonomic names to unknowns. Mycologists have long been a vocal group in arguing for improving the accuracy of names used in Gen-Bank  (11, 12).
In addition, biologists have expressed concern about the lack of associated voucher data in many GenBank entries  (13). Although a specimen voucher qualifier has been available and promoted by GenBank since 1998  (14) , this remains poorly used by submitters. To improve this, GenBank now recommends applying a version of the Darwin Core standards  (15) , which intends to facilitate the sharing of information about biological diversity through reference definitions (e. g. a standardized specimen voucher format) for relevant data. Where feasible, this will apply to any biorepository data shown in the 'specimen_ voucher', 'culture_collection' and 'bio_material' qualifiers of a GenBank sequence accession  (14). This format also allows for vouchers to be linked directly from a sequence accession to a dedicated specimen or culture page at the relevant biorepository (where available), and it improves traceability across different databases.
A number of additional specialized databases focused on specific marker sequences have been built to further enhance sequence accuracy. Mycologists have used DNA sequence data for testing species-rank hypotheses for over 20 years. The internal transcribed spacer (ITS) region containing two spacers (ITS1 and ITS2) flanking the nuclear ribosomal 5. 8S gene has been an especially popular marker  (16). A curated ITS database focused on human and animal pathogenic fungi was established at www. mycologylab. org for the International Society of Human and Animal Mycology (ISHAM). Initially, the UNITE database (http:// unite. ut. ee/) had a similar functional focus on ectomycorrhizal ITS sequences  (17). Since then, it has expanded to provide tools for assessing sequence quality and Webbased third-party sequence annotation (PlutoF) to published sequences for all Fungi.
The UNITE database now acts as a GenBank mirror for all fungal ITS sequences and has a particular focus on integrating sequences from environmental samples into reproducible taxonomic frameworks  (18). Among other databases with similar aims, ITSoneDB focuses on ITS1 sequences  (19) , whereas the ITS2 database houses ITS2 sequences and their 2D structures  (20). A number of additional publicly available online databases favor other sequence markers for fungal identification, e. g. the large and small nuclear ribosomal subunits (18S, 28S) and fragments from the translation elongation factor 1-alpha gene  (21, 22). Several of these databases are focused on specific taxonomic groups  (23) (24) (25). The DNA barcoding movement made an important impact on sequence accuracy by promoting a clear set of standards for DNA barcodes: raw sequence reads and reliable sequence data combined with a correct taxonomic name as well as collection and voucher information  (26, 27).
The Barcode of Life Data System (BOLD; 28) has a significant amount of sequence data that overlap with GenBank and was explicitly set up for DNA barcoding. The CBS-KNAW Fungal Biodiversity Centre, MycoBank and the recently launched BOLD mirror, EUBOLD, are also proposing online identification tools that can compare unknown sequences simultaneously against several reference databases. Despite its long history of usage, mycologists have only recently proposed the ribosomal ITS region as a universal DNA barcode marker for Fungi  (29). This means that regardless of several limitations  (30) , ITS will likely remain the main marker of choice for fungal identification in the immediate future. Since 2012, the ITS region has specifically been used for species identification in numerous DNA barcoding studies on a variety of fungal groups ranging from mucoralean fungi  (31)  to common molds such as Aspergillus and Penicillium  (32).
(41). This relies on character comparisons from at least three unlinked loci. In comparison, the DNA barcode approach relies on less rigorous analysis techniques using universally sampled sequences from only one or rarely two markers. The focus in DNA barcoding is on obtaining limited sequence data from the largest possible number of specimens. It is most efficient in specimen identification, used in concert with a well-validated database containing accurate species delimitations  (42). However, where information on species boundaries are lacking, it can also be used for initial species discovery. In line with this, it is our intention to maximize the accuracy of the sequences available for specimen identification and to emphasize where more sampling is required during species discovery.
Selecting reference sequences DNA barcodes per definition, have to be backed up by publicly accessible raw data files (trace data), and, if they are linked to type material, have the potential to act as reference sequences that also provide a higher confidence in sequence accuracy. However, many other important sequences are already available in the public databases that would not be qualified as official barcodes. The need to communicate specific levels of confidence in sequence accuracy has yielded proposals for a quality scale in sequences  (43) , but establishment of such a system remains elusive. Since 1 January 1958, any validly published species name is connected to a type, which should be treated as primary reference. A type can principally be an original depiction of a species, though then it is good practice to designate a separate specimen as a neotype, or epitype where appropriate.
However, in the majority of cases, a type will be a physical specimen. Type specimens are the only specimens to which one can reliably apply the original name, thereby providing a physical link to all other associated information. Having an ITS sequence or other marker sequences connected to a reliable publicly accessible representative of the species thus provides researchers with a reference point to a specific name. This makes it possible to unambiguously communicate findings with the research community and provide the opportunity to generate additional related data and expand current collections. At GenBank, a particular challenge has always been the annotation of sequences derived from type material. Until recently, there was no standard means to specify typerelated information during the process of data submission.
Notes can be added to individual accessions, but they remain cumbersome to uncover in queries. In this article, we describe efforts to address this shortfall by expanding fields to indicate type material in the National Center for Biotechnology Information (NCBI) Taxonomy database. A number of ITS sequences were re-annotated and formatted in a separate curated database at NCBI, RefSeq Targeted Loci (RTL). This database was originally set up as a repository for bacterial type sequences obtained from the databases RDP, SILVA and Greengenes. It was subsequently expanded to Fungi-initially using a divergent set of sequences generated by the collaborative Assembling the Fungal Tree of Life project (AFToL)  (44). We release an initial reference sequence set of nearly 2600 ITS accessions covering $2500 species for inclusion in RTL.
Materials and Methods Verification steps for RefSeq data set: Verification was done in the following order with each step building on the information of the previous step (Figure  1 ). 1) Collecting ITS records for evaluation. Lists of potential ITS accessions from type and verified specimens for display in RefSeq were generated in several ways via Entrez queries in the NCBI Nucleotide database, daily taxonomy curation and collaboration with experts in the fungal research community. 2) Sequence quality. All accessions were verified with the Perl script ITSx  (46)  to ensure sequence continuity including the ITS1, 5. 8S and ITS2 regions. A record was excluded if it had an incomplete ITS2 region (as inferred by ITSx) and incomplete ITS1 region, which had no conserved CATTA-like motif at the 5 0 end (within 40 bases of the end), and the length was <80% of the average complete ITS region (annotation as inferred by ITSx) for the taxonomic order to which it belonged.
We only considered one of the following types per species: holotype, isotype, lectotype, neotype, epitype, syntype and paratype. The holotype is a single specimen designated by the original author at the time of a species description. The other types indicate a variety of relationships to that specimen or can serve as replacements in certain circumstances (see glossary of the ICN for details: http://www. iapt-taxon. org/ nomen/main. php?page¼glo). Where we could not clearly distinguish the kind of type, these are annotated only as type. For the verification of type status, we relied mainly on the information at culture collection databases listed in Table  1  and the nomenclatural databases, MycoBank and Index Fungorum, as well as experts in the fungal research community. The main source of type status information was publications.
Type status information can currently not be extracted from publications in a high-throughput manner, and the documents themselves are not always freely accessible, making curation efforts time consuming and heavily dependent on manual curation. Where possible, types tied to the original species description (protolog) of the currently accepted name were selected. Ex-type: Living cultures do not have the formal nomenclatural status of a type specimen, but sequences obtained from cultures that were derived from type specimens were also indicated; where possible, it was indicated from what kind of type collection these originated. Details on such extype cultures and type specimens are both included under 'type material' in the NCBI Taxonomy database. Type identifiers in the NCBI Taxonomy database can include both heterotypic synonyms (also referred to as taxonomic or facultative synonyms) and homotypic synonyms (also referred to as nomenclatural or obligate synonyms).
However when possible, we combined and annotated heterotypic types from asexual and sexual morphs (anamorphs and teleomorphs) from the same species in order to promote nomenclatural stability. An example is indicated in Supplementary Material (Supplementary Figure  S1 ). The taxonomic names in current use were identified by consulting the latest publications, acknowledged taxonomic experts, culture collection databases as well as MycoBank and Index Fungorum. Where possible, a script using cURL (http:// curl. haxx. se/) was used to extract type status and names from databases such as CBS and MycoBank. 5) Sequence identity. This is not the first attempt at verifying data in INSDC, and thus we relied on the data from the UNITE (version 5) and ISHAM databases to help verify sequences. Also, the sequence identity of selected INSDC records that could potentially be represented in RefSeq was compared with other sequences from type specimens.
These were identified via type specimen identifiers obtained from MycoBank (compared with the isolate, strain, collection and specimen voucher fields) and from daily taxonomy curation. Finally, any type material data were uploaded as permanent name types in the NCBI Taxonomy database. Sequence identity was considered accurate, and a sequence was considered to be associated with the type specimen if one of these conditions were met: • There was >99. 5% identity over >90% of the ITS region in the potential RefSeq sequence compared with another type specimen sequence of the same TaxID in GenBank using megablast alignments. Instead of using 100% identity, we used 99. 5% to accommodate for a small number of non-ATGC characters. Each sequence record is associated with one TaxID, and the TaxID represents one taxon that in NCBI taxonomy can Possible misidentifications/labeling of accessions (not verified above) were investigated for the following: • Sequences that were >99.