dataesr/scientific-paragraphs-categorization huggingface dataset:
5% identical over >90% of the ITS region to more than one type sequence identified in GenBank or RefS/RepS from UNITE of a different TaxID using megablast alignments. • Sequences that were <98. 5% identical over >90% of the ITS region to RefS/RepS from UNITE of the same TaxID using megablast alignments. • Same accessions associated with different TaxIDs in GenBank and UNITE. Further investigation was necessary if more than one ITS accession were available for a type, and one or more copies were <99. 6% identical to the sequence selected for representation in RefSeq. This was done to ensure that the selected sequence was not the outlier in the group, which may be the result of low sequence quality or mislabeling. Sequence copies were aligned using MAFFT (http://www. ebi. ac. uk/Tools/msa/mafft/) and viewed in BioEdit  (48)  to determine which sequence contained the bases that are at odds with the rest.
Reformating of accessions for RefSeq Each ITS record was re-annotated with ribosomal RNA (rRNA) and miscellaneous RNA (misc_RNA) features representing the boundaries of the rRNA and the ITSs as predicted by the ITSx Perl script. Lists of ITS records with metadata provided by experts were compared with metadata in the original GenBank submission. Source features were reformatted, corrected and augmented with information where needed. Culture collection specimens entered in the strain or isolate fields were moved to the culture collection field. Similarly, any herbarium specimen information was moved to the specimen voucher field. If the original GenBank submission contained no identifier from a collection in the NCBI Collections database, then the appropriate public collection identifier obtained from the original species description was added to the RefSeq record.
Collection codes used in the culture collection and specimen voucher fields followed the acronym format used by GenBank indexing (the NCBI Collections database available at http://www. ncbi. nlm. nih. gov/projects/ BioCollection/search_collection. cgi). Both these fields were formatted appropriately with the code separated with a colon from the collection's correct identifier. If a dedicated specimen page was available online, with the collection identifier in the URL, direct links to the culture collection database could be made available when the correct format was used. Google searches for the presence of online databases of all collections associated with this data set were performed and specimen specific pages identified. The note field for each record was augmented with type status information, which included the type category (holotype, isotype, etc.
Type status Metadata associated with accessions in lists provided by mycology experts were compared with source metadata of these accessions in GenBank at NCBI. Conflicting information (e. g. collection/specimen identifiers) was resolved by updating the GenBank record (if submitted to GenBank and the original submitter was involved) or the RefSeq record. When the correct information was not rapidly  discernable, records were excluded from further analysis. Type status information of culture collection identifiers or specimen vouchers provided by the community was also compared with taxonomy/collection databases and publications. This curation process involved the research community and curators at culture/herbarium collections to resolve conflicting or missing information. Similar to the process in GenBank, culture/herbarium information from recently published research is not released publicly until collection curators receive notification or find the associated publication in the public domain.
In addition, even though more and more culture/herbarium information is digitized, backlogs often exist. Thus, the absence of culture/herbarium numbers at an accessible online database does not necessarily imply a dead, contaminated or misidentified specimen. Only a small portion of the conflicting type specimen identifier information or absence was attributed to typographical errors or dead/contaminated cultures (14 identifiers). Where possible, we excluded types of heterotypic synonyms (see Supplementary Figure  S1 ), as explained in following curation steps.
Current taxonomic name Identifying homotypic synonyms involved collecting the name by which a type specimen was first described, the name with which this specimen is currently associated and finally the original name (basionym) of that current name. Names provided by experts in the research community were compared with those in GenBank records, as well as other collection and taxonomy databases. The original name of the type specimen had to be the same as the current name or basionym and, if not, it needed to be a homotypic synonym of the current name to be considered for inclusion in this RefSeq set. The majority of this current name information (92%) was easily accessible with a script from MycoBank, and $56% of the original names of type specimens were accessible from collection databases.
However, any remaining information required a manual labor-intensive effort to obtain or verify names from publications or less accessible databases. This step in the curation process revealed many discrepancies between databases (and publications), which included orthographic variants, a need for taxonomic updates and spelling or labeling mistakes. Most discrepancies were resolved by addressing these issues at NCBI Taxonomy, external taxonomy and collection databases involving the respective curators. At publication time, 94% of RefSeq ITS records used the same current name that MycoBank or Index Fungorum used, and the rest used published names that were not public at both databases (1%) and different/not designated as current name at Index Fungorum (5%).
Sequence identity Sequence identity of UNITE's curated list of RepSs or RefSs were compared with those in GenBank selected for RefSeq curation. The UNITE database uses a centrality test to verify sequence identity and evaluate curation. However, because of filtering steps at UNITE and newly described species with a unique ITS sequence, not all RefSeq accessions are present in UNITE or associated with a species hypothesis (SH) (Figure  3 ). Comparisons against selected type sequences in GenBank verified the sequences selected for RefSeq at type specimen level making sure the best sequence for the specimen was selected. Comparisons identified classification discrepancies between MycoBank, Index Fungorum (used by UNITE) and NCBI Taxonomy, which have been communicated among the different curation databases.
This comparison step also identified discrepancies in voucher or species names between the GenBank record and the publication, which could then be corrected. Sequences that were >99. 5% identical and had over 90% overlap of the ITS region with more than one type sequence in GenBank or RefS/RepS from UNITE under a different TaxID were investigated. Discrepancies mostly revealed the existence of closely related species, which have been noted in a publication or by experts in the fungal research community. Thus, for these cases, there was no problem with the identity of the specimen under the classification point. Sequences that were <98. 5% identical and had over 90% overlap of the ITS region to RefSs/RepSs from UNITE of the same TaxID Accessions in UNITE with a Species Hypothesis Code Accessions in UNITE but no Species Hypothesis Code Accessions not in UNITE were also investigated.
Reformatting accessions for RefSeq All   4 ). About 250 records were edited to correct collection/ specimen voucher information or to add a collection number from a public collection. After curation, all records contained a culture collection or/and specimen voucher identifier in the correct field. Sequences originated from material kept at 159 collections of which only 32% had a searchable public database. However, most ($75%) of the records were associated with material from collections with a public database (Figure  5 ). A small number of collections had a specimen page URL that includes the collection number and to which a link can easily be formatted. Before curation started, links existed to five biorepositories. Additional links were added, and the full list of biorepositories with their acronyms indicated is in Table  1.
Changes to NCBI databases The NCBI Taxonomy database (http://www. ncbi. nlm. nih. gov/taxonomy) acts as the standard nomenclature and classification repository for the INSDC. It is a central core where taxonomic information for the entries in other databases-such as GenBank-is stored. NCBI Taxonomy uses an array of name classes, e. g. 'scientific name', 'synonym', 'equivalent name' to express various taxonomic attributes  (57). An example of a taxonomic record is shown in the Supplementary Material (Supplementary Figure  S2 ). Two specific name types unique to fungi, 'anamorph' and 'teleomorph', but falling out of favor (58), will slowly be phased out as fungal classification adapts to a new nomenclatural system. An additional name type was recently added to the taxonomy database, 'type material'.
This information is indexed so that related sequence records annotated with type specimen or ex-type culture identifiers with synonymous (homotypic and heterotypic) species names can be found with an Entrez query. The following Entrez query 'sequence from type[filter] AND fungi[orgn]' will list all fungal taxonomic entries (from all genes and genetic markers) with type material attributes. The same query can be used to do a limited BLAST search on sequences from type material. Currently (March 2014), this covers over 150 000-nt sequence accessions in INSDC databases, including several additional regions besides ITS. This includes genome sequences and RefSeq messenger RNA records. In the era of phylogenomics, researchers may also be interested to know which Accessions from specimens with direct links to specimen pages Accessions from specimens with internet accessible database Accessions from specimens with no internet accessible database  genomes are from type specimens and the associated proteins.
In the future, the Entrez Protein Clusters database will also include fungal protein accessions, and those originating from type specimens can be marked as such. In addition to fungal type data, there are now >500 typeassociated entries for metazoa and already >500 000 for bacteria. NCBI Taxonomy currently lists >28 000 binomial fungal names at species rank, and 56% had good quality (not chimeric or broken) ITS records in GenBank (including synonyms). Our current data set of RefSeq sequences represents 16% of binomials with clean ITS data. In terms of classification (regardless of presence or absence of ITS data), the RefSeq set covers 660 of 4387 possible fungal genera, 249 of 514 possible families, 120 of 153 possible orders and 36 of 37 possible classes. With continued curation, more types will be identified and the associated sequences added to the RefSeq database.
The presence of curated type material improved the efficiency of taxonomic updates at NCBI. The validation of sequences and type material released in RefSeq allowed >300 taxonomic names to be merged, rectified or updated in NCBI Taxonomy. Several taxonomic names that were submitted with a genus and strain identifier only and not updated upon publication could easily be verified and updated by relying on accurate specimen data present in their sequence accessions. Similarly, curating and knowledge of synonyms are important because it can greatly influence the accuracy of any microbiome or ecological study. Recent studies on the oral microbiome provide a good example  (59). Several researchers still continue to use large polyphyletic genus names to discuss species of clinical importance  (60).
Standards for traceability of specimen vouchers The most time-consuming step in this curation process was to identify and verify type specimens and cultures. It was useful to import type identifiers from, for example, MycoBank, but identifiers must still agree with the metadata in the GenBank records. Using the same identifier from a specific collection (especially when specimen vouchers from herbarium material are involved) and a standard structure among various sources such as taxonomy databases, collections, publications and sequence records will contribute tremendously to improve this process. Listing type specimen identifiers in the abstract of a paper represents another helpful measure to avoid having type information hidden behind a paywall. Using an Entrez query such as this: (collection cbs[prop] OR cbs[title] AND fungi[orgn]) AND (2014/01/01: 3000[PDAT]) can help CBS collection curators, for example, to identify newly released sequence records since the beginning of 2014.
NCBI Collections The ability to provide direct links between GenBank and biorepositories (herbaria and fungaria, natural history collections, zoos, botanical gardens, biobanks, culture collections and others) relies on using unique identifiers to denote cultures and specimens. The potential pages to target with links have been expanded by several projects aimed at increasing the digital presence of a number of institutions. For example, the Mycology Collections data Portal (MyCoPortal; http://mycoportal. org/) provides direct access to digitized specimens records provided by The Macrofungi Collection Consortium, a collaboration of 35 institutions in 24 states in the USA (http://mycoportal. org/portal/index. php). The Global Plants Initiative (GPI) is another such effort, housed at the Royal Botanic Gardens, Kew.
This is an international partnership of more than 300 herbaria in 72 countries. GPI's goal is to digitize and provide access to type specimens of plants, fungi and algae through community-contributed JSTOR Global Plants online database (http://plants. jstor. org). Other resources include Straininfo, which databases information related to cultures and strains  (61). NCBI has retained a record of all biorepositories to assist indexing of submissions in the NCBI Collections database (http://www. ncbi. nlm. nih. gov/projects/BioCollec tion/search_collection. cgi). The majority of fungal-related acronyms rely on unique identifiers of herbaria indexed at Index Herbariorum  (62) , whereas the majority of culture collections are listed in the directory of the World Federation for Culture Collections (WFCC).
At NCBI, these unique identifiers are also used for museum collections. These multiple sources often contain redundant identifiers, so it is necessary to provide unique versions. This was achieved by adding a country abbreviation in angular brackets. For example, BR<BEL> was used to distinguish the National Botanic Garden of Belgium from the Embrapa Agrobiology Diazothrophic Microbial Culture Collection, BR<BRA>. For the present, it is more practical for NCBI to continue usage of this resource for its own curating and indexing functions. Another effort, the Global Registry of Biorepositories (GRBio) has been supported by the Consortium for the Barcode of Life (CBOL). This currently lists >7000 biorepository records by combining data from CBOL, Index Herbariorum and the Biodiversity Collections Index.
Application of Darwin Core and other standards Darwin Core is a data standard for publishing and integrating biodiversity information  (15). The Darwin Core standard triplet format for specimen data consists of a structured string containing an institutional ID, collection code and catalog ID, all separated by colons. Currently, NCBI uses unique labels from the Collections database  (14). In many cases, a secondary collection code (such as a collection devoted to Fungi or Plants at a specific institution) is not necessary. In the example given above, the ex-type culture of Colletotrichum brevisporum is indicated as a doublet only, e. g. /specimen_voucher¼"BR<BEL>: 70109". It is now possible to register typification events at MycoBank. MycoBank Typification numbers for the designation of lectotypes, epitypes and neotypes can be obtained and referred to in publication  (63).
DNA barcoding and standards for GenBank submissions The ITSx script  (46)  has been a helpful and time-saving tool in curating the ITS records. It has also provided an important quality control tool for anyone downloading and submitting ITS sequences. The script is efficient to confirm complete ITS regions if enough nucleotides are present in the 18S and 28S region, otherwise curation time needs to be spent to verify the coverage. In addition, sequences were also screened for non-ATGC characters, but ideally one would also like to be able to view sequence traces and be assured about the quality of the base calls. Currently, this information is not available for any ITS sequence. The standard for a DNA barcode (http://www. barcoding. si. edu/PDF/DWG_data_standards-Final. pdf) contains a set of sequence quality requirements in addition to increased scrutiny of specimen data.
Part of this involves the deposit of trace data in addition to the sequence deposit at the INSDC. Currently, GenBank will assign a BARCODE keyword to sequences that meet these standards. However, many sequences continue to be referred to as DNA barcodes in the literature without meeting all these requirements. The deposit of sequence traces is a crucial missing element, and it is not likely to see an increase in the foreseeable future. Many highly significant sequences from types and other important specimens already exist in the INSDC databases. Sequences selected as part of this article should meet all the standards for a DNA barcode except for the deposition of trace data. It should therefore be also possible to use these sequences as 'barcode-like' or reference sequences, although they would not formally qualify for barcode status.
Defining types and reference sequences Currently, the public sequence databases include a mix of sequences derived from type and non-type strains and with various degrees of curation and certainty. An improved and expanded nomenclature for sequences has been proposed elsewhere  (41) , based on an earlier proposal for 'gene types'  (84). This work was done with a zoological perspective, addressing concepts formulated under the International Code of Zoological Nomenclature. To continue this discussion and present a system applicable to species codified under the ICN, we propose a simplified framework for consideration. Following this concept, species can be divided into several categories according to the combination of the type/reference strain status and of the sequence length/quality. Sequences from type material should, when possible, be used preferentially for identification purposes, whereas the other sequences can be used for the description of the beta diversity within the species.
A comprehensive length/ quality index (LQI) could be defined by a simple equation: LQI ¼ ðSL À DSÞ=LT where SL is the actual sequence length, DS the number of degenerated sites and LT the minimal sequence length to obtain a sound classification. According to this LQI parameter, all the sequences currently presented in the RefSeq database exceed the minimal requirement for robust identification. In general, sequence databases could be managed according to simple rules, defining a hierarchy of sequences according to their origin, for example: 1. Type/reference sequences with high LQI are used for any purpose and serve as potential targets for the RefSeq database. 2. Type/reference sequences with low LQI are used for identification with a warning on the identification quality until they can be replaced with better sequences.
It follows logically that if the same link can be made for DNA sequences, these sequences can provide reliable reference points for names in computational comparisons. In this article, we have focused on the re-annotation of a taxonomically diverse set of marker sequences such that a clear link between a species name, a specimen or culture and its sequences can be established with a high level of certainty. The most important part of this process is the increased focus on specimen and culture annotations using a standardized format that can be traced across multiple databases. We used a number of redundant steps in the curation process to remove errors. Yet as is true for any database, some will remain. Because RefSeq is a fully curated database, relying on selections made by taxonomists at NCBI in consultation with a range of experts, it will also be simple to remove questionable sequences as soon as we are aware of them.
Feedback about incorrect RefSeq records can be received here: http://www. ncbi. nlm. nih. gov/projects/RefSeq/update. cgi. There is a substantial and growing increase in the number of sequences being deposited in public sequence databases without scientific binomials  (10). To better distinguish truly novel lineages from poorly identified ones, an accurate set of reference sequences will be essential. The manual curation performed in this study relied on mining the information from a variety of resources, including the associated literature. This scales poorly beyond a few thousand entries. For this reason, we focused on a manageable subset of reference sequences focused on ties to type material. It is hoped that machine learning techniques, as already applied to taxonomic names from literature  (92) , can also improve specimen and, specifically, type material annotation in the future.
Our initial data set of $2600 ITS records should provide a valuable training set for such techniques. It is projected that there are $400 000 fungal names already in existence. Although only 100 000 are accepted taxonomically, it still makes updates to the existing taxonomic structure a continuous task. It is also clear that these named fungi represent only a fraction of the estimated total, 1-6 million fungal species  (93) (94) (95). Moving forward, as new species are being described, this process must be documented in a more efficient manner, keeping track of the type specimen information in association with its sequence data. Submitters of newly generated fungal ITS sequences are also asked to consider previously published guidelines  (96, 97). We propose the following steps in submitting future type-related data as part of a normal submissions process to GenBank and the nomenclature databases.
It is important to emphasize that Refseq selections will only happen after submission to INSDC databases and does not require a separate user-directed process. 1. Where possible, submitters can alert GenBank indexers to the presence of type material and include a table during their submissions: <species name>\t <type strain/specimen>\t <type of type>, for example: Aspergillus niger \t ATCC 16888 \t ex-neotype Agaricus chartaceus \t PERTH 07582757 \t holotype Saccharomyces cerevisiae \t CBS 1171 \t ex-type 2. If using ITS sequence data, use Figure  4  annotation as an exemplar during GenBank submission, applying annotations determined by the ITSx script. 3. Register typification with correctly annotated specimen numbers in an available database, e. g. MycoBank. 4. Verify that the format for specimens and ex-type cultures in GenBank match that in the published record as far as possible.
5. Extend the principles for traceable specimen and culture data during species descriptions in mycological journals. Correctly formatted type specimen identifiers from public culture/herbarium collections should not be limited only to ITS records but also any other sequence records including genome records. Genome sequencing centers use ITS regions to confirm the identity of the fungus being sequenced. It is a good practice to include this with a genome assembly. However, the ribosomal cistron is often omitted because of difficulty to establish the exact copy number and the positions of the multiple copies in the genome. The RefSeq ITS set has already been applied in improving genome assembly quality at NCBI by identifying contamination in genome assemblies, especially in obligate biotroph genomes.