dataesr/scientific-paragraphs-categorization huggingface dataset:
The lack of common glycomics standards has hindered progress in representing information stored in databases and hampered data exchange and interoperability of such data-bases. Several cooperative initiatives for representing and collecting glycomic data have been launched in response to this situation. An international glycan structure repository named GlyTouCan was released to become a community resource. 7 s a first step in adopting a standard view on glycans, it relies on the depiction of 2D structures in the SNFG notation increasingly shared within and outside glycoscience and applicable to representing GAGs. Furthermore, semantic Web technology, commonly used in bioinformatics via Resource Description Framework (RDF) data modeling, is implemented as a new standard for representing and storing knowledge in various databases.
At the time there were only vendor formats for raw mass spectrometry data and a few oversimplified plain text formats specific to the software tools of the time. Yet it was recognized that standardized formats would allow not just tool interoperability, but also promote the sharing and reuse of data between laboratories. The mission of the PSI was, and still is, to bring together tool developers from academia, software vendors, and hardware vendors to create, maintain, and promote data standards that will be used throughout the proteomics and computational mass spectrometry community. These products include standardized data formats, minimum information guidelines, and controlled vocabularies (CVs) used to drive the formats. Standard formats are only effective if they are widely implemented in software tools, and thus the PSI also includes extensive outreach efforts and works with software developers to implement its standards.
As a result, adoption and widespread implementation of PSI standards has enabled the development of software, such as Cytoscape, and APIs (Application Programming Interfaces), such as PSICQUIC  12  and ProXI, which enable easy access to rich data streams by a broad spectrum of the research community. In this article we first provide an overview of the operation of the PSI, highlighting its most recent workshops. We then describe the CVs, guidelines, and data formats that have been developed and ratified by the PSI over the years (summarized in Table  1 ). Next, we describe the set of standards that are currently in various phases of development, with an open call for participation by anyone willing to contribute to our efforts. Finally, we provide a brief discussion of synergies with other related organizations in the life sciences community and conclude with a vision of future contributions to the field.
■ CONTROLLED VOCABULARIES AND ONTOLOGIES An ontology is a collection of concepts with names and definitions and clear relationships between all the terms, typically with "is a" and "part of" relationships (e. g. , a wheel is a part of a car, and a car is a vehicle, and a vehicle is a thing, although typically much more complex). A crucial component of the ontology is the relationships. A similar collection of concepts where the focus is on the concept names and definitions and not the relationships is typically thought of as CV. Thus far the PSI concept collections, widely used as proteomics-related ontologies,  14  are part way between ontologies and CVs and are described further below. The PSI-MI (Molecular Interactions) CV was first published in 2004 15 and, since then, has been regularly extended to encompass new experimental methodologies and to serve extensions made to the formats to accommodate new data types.
The CV is maintained on GitHub (https://github. com/ HUPO-PSI/psi-mi-CV/blob/master/psi-mi. obo) and is readily available through the Ontology Lookup Service (www. ebi. ac. uk/ols/ontologies/mi) and BioPortal (https://bioportal. bioontology. org/ontologies/MI). An issue tracker on GitHub enables new term or update requests to be submitted by the user community. Use of the PSI-MI CV is an integral step in describing interaction data using the PSI-MI formats. The PSI-MS (Mass Spectrometry) CV was initially developed to serve the needs of the PSI mass spectrometryrelated data formats, most of which make extensive use of CV terms to precisely describe metadata and provide extensibility as technologies advance. 16 The CV was first developed to support the now-deprecated mzData format and then for its replacement mzML,  17  and has since been adapted for numerous additional formats that will be further described below.
It contains over 3,300 terms for specific instrument models, software packages, and other metadata concepts and continues to grow as more such terms become available. This CV is readily accessible at https://github. com/HUPO-PSI/ psi-ms-CV/ and is typically updated at least monthly. The contents of the CV is also browsable via the Ontologies Lookup Service  18, 19  (https://www. ebi. ac. uk/ols/ontologies/ ms) and the NCBO BioPortal  20  (https://bioportal. bioontology. org/ontologies/MS). PSI-MOD is an ontology of modified amino acid residues. 21 he 2,116 terms focus on the end products of modifications rather than modifications themselves. Thus, instead of terms for phosphorylation and oxidation, there are terms such as Ophospho-L-serine and L-methionine sulfoxide. The concepts are organized in several hierarchies by amino acid and by modification type.
Although the ontology suffered from a period of inactivity several years ago, volunteers have now stepped forward to maintain it actively. The ontology is maintained on GitHub (https://github. com/HUPO-PSI/psimod-CV) or is readily available through the Ontology Lookup Service (https://www. ebi. ac. uk/ols/ontologies/mod). Complementary CVs, maintained by other organizations, which contain information on protein modifications include RESID,  22  PTMList (https://uniprot. org/docs/ptmlist. txt), Unimod,  23  and XLMOD. 24 PSI-MOD was originally based on RESID, which is now mostly deprecated and used by very few tools. UniProtKB (UniProt KnowledgeBase) uses its own PTMList resource (https://uniprot. org/docs/ptmlist. txt), although PTMList is substantially synchronized with PSI-MOD. The popular Unimod community resource of mass modifications (http://unimod.
org/) instead focuses on the modifications themselves (with terms like "Phospho" and "Oxidation") and is a flat CV with no relationship structure. The XLMOD CV (https://github. com/HUPO-PSI/xlmod-CV) is a simple collection of known chemical cross-linkers for use with formats that need to describe which cross-linker was used in the sample handling. All these ontologies and CVs are maintained in the OBO format. However, each commit is versioned with a new minor release number and an OWL format file is autogenerated using the ROBOT conversion tool (http://robot. obolibrary. org/ convert. html) via GitHub actions. Assistance with maintenance of the CVs and ontologies is a good entry point for those with proteomics domain knowledge who wish to begin contributing to the PSI.
■ GUIDELINES In addition to data formats and CVs, the PSI has also developed several sets of guidelines. These guidelines typically describe at minimum which pieces of information should be provided when releasing or sharing data, without specifying the encoding for that information. This minimum information may be provided in the text of an article, in an article's Supporting Information, or in a PSI standard format. PSI standard formats are often designed with the aid of previously developed guidelines, ensuring that they are capable of capturing at least all of the minimum information and usually much more. The first standard published was the Minimum Information about a Molecular Interaction eXperiment (MIMIx), which advises the user on fully describing a molecular interaction experiment, in either a publication or a database, and lists which information is important to capture.
These MIAPE components were implemented in some systems such as the ProteoRed database  32  and used as a guide in other software and during the development of formats. However, it seems that while most researchers would like others to provide rich metadata about their data sets, most researchers are reluctant when asked to provide all that information about their own data sets and avoid systems which require that they do so. In practice, the MIAPE guidelines have significant overlap with minimal reporting guidelines/checklists developed by individual journals (e. g. , https://www. mcponline. org/ mass-spec-guidelines for Molecular and Cellular Proteomics and http://pubsapp. acs. org/paragonplus/submission/jprobs/ jprobs_proteomics_guidelines. pdf for the Journal of Proteome Research). These journals apply these guidelines to encourage or enforce that particular details are provided at least in Methods sections.
Given the wide range of journals publishing proteomics data sets, it is likely an unsolvable problem to get all journals to sign up to a shared set of guidelines. Although not formally ratified by the PSI, the PSI supported the development of the HUPO Human Proteome Project (HPP) Mass Spectrometry Data Interpretation Guidelines. Three such versions have been produced. The 1. 0 version of these guidelines described the repository deposition requirement for data contributed to the HPP (https://hupo. org/ HPP-Data-Interpretation-Guidelines). Version 2. 1 of the guidelines added additional requirements for false-discovery rate (FDR) thresholding and for evidence supporting claims of detection of human proteins. 33 Version 3. 0 of the guidelines further refined these ideas to provide more stringent requirements for exclusion of false positives.
■ EXISTING STANDARD DATA FORMATS The PSI has developed numerous standardized data formats in the past 20 years and more are currently under development (Table  1 ). An overview of the formats developed by the Molecular Interactions Working Group and their relationships to other components is summarized in Figure  1. The formats of the Mass Spectrometry Working Group and the Proteome Informatics Working Group and their relationships to other components are summarized in Figure  2. In this section we briefly describe each format, assess its current status, and provide links and citations for obtaining more information. Active formats are presented by working group, followed by non-PSI related formats and deprecated formats.
Molecular Interactions Working Group PSI-MI XML. The MI group released an XML standard (PSI-MI XML) in 2004,  15  which allowed the basic information about a protein-protein interaction experiment to be captured and transferred between data resources or visualization/ analysis tools. This initial, very simplistic representation was upgraded in 2007 to enable a full capture of the details of any experiment, including in silico and predictive data, which describes an interaction between any number of biomolecules, including experimental details, molecule details (affinity tags, binding sites, amino acid mutations, etc. ), and the host organism in which the experiment is undertaken. Additional information, such as kinetic parameters or the method by which a molecule is delivered or engineered into a cell can also be added, if required.
35 The PSI-MI XML 2. 5 version of the format remains the main workhorse by which the majority of interaction data is exchanged between resources, and enables all of the above use cases. As more specialist use cases have arisen which could not be fully captured in this format, in 2018 a new, backward compatible version, PSI-MI XML 3. 0, was developed. 36 This version can be used to describe, for example, the details of a fully curated multiprotein complex with subunit topology, including binding regions, and stoichiometry or to link kinetic parameters to amino acid mutations, sequence deletions or insertions. MITAB. Following requests from bench scientists for a simpler version of the PSI-MI XML format for use by researchers not experienced in working with XML files, the MITAB format was developed to enable most aspects of a molecular interaction experiment to be described.
The format shares usage of the PSI-MI CVs and many fields are identical to those in the XML formats, but the data is described in tabdelimited format with increasing number of columns in the different versions (MITAB 2. 5, 2. 6, 2. 7, 2. 8) allowing increased data capture. The most recent version, MITAB 2. 8 also referred to as CausalTAB, enables the representation and dissemination of signaling information through the description of the causality of an interaction. MI-JSON. MI-JSON is the recommended protocol for serving interaction data to web pages and visualization tools. The format is described at https://github. com/ MICommunity/psi-jami/blob/master/jami-interactionviewerjson/schema/mi-json-schema. json. Java Software Library JAMI. JAMI 37 is a single Java library and framework which unifies the standard formats such as PSI-MI XML, PSI-MITAB, and MI-JSON as well as formats not created by the PSI.
Mass Spectrometry and Proteomics Informatics Working Groups mzML. The primary standardized format for encoding the output of mass spectrometer instruments is mzML. 17 All instruments write out their primary data in a binary vendor format. Most vendors provide software libraries to read their data files, but these are often only available on the Microsoft Windows platform. In order to facilitate data analysis on any platform, and ensure that data files could always be read, the PSI developed the open XML-based format mzML. Version 1. 0 was released in 2008 and a minor fix version 1. 1 was released in 2009; version 1. 1 has been stable and widely used ever since. The focus of mzML has always been universal readability, and thus small file size and fast access speed have not been the primary design drivers.
As a result, numerous alternatives to mzML that improve on file size and access speed have been proposed,  [38] [39] [40] [41]  although none seem to have gained substantial usage, perhaps in part because of their dependencies or complexity. A variant of mzML called imzML  42  has become quite common in the imaging MS community, and it is nearly identical to mzML except that the spectra are stored in a more efficient sidecar file instead of the main file. In order to try to consolidate on one improvement over mzML, the PSI is considering formally approving the HDF5-based mzMLb format  43  as a PSI standard in addition to mzML. The mzMLb format has exactly the same schema and encodes metadata in the same way, and thus interconversion is easy. Via its use of HDF5, which automatically incorporates compression, file sizes are much smaller than mzML and random access to spectrum within the file is also much faster.
Adding mzMLb to existing tools is relatively straightforward if the HDF5 dependency can be included. Ongoing Work: mzML Extension for DIA and IMS Data. As described above, the mzML format has been stable and widely used since 2009. At the time, data independent acquisition (DIA) and ion mobility spectrometry (IMS) were not widely used and not explicit factors in the design. Now that they have become widely used, there is great interest in extended mzML for use with these technologies. Fortunately, the schema definition does not need to be changed, and good support for these technologies can be achieved with some additional CV terms and an explicit best practices document that describes how these types of data should be encoded in mzML. This best-practices document has been drafted and is nearly ready for submission to the DocProc.
The current draft is available at the mzML web page (https://psidev. info/mzml/ ). mzIdentML. The primary PSI standard format for encoding the peptide/protein identifications that are derived from an MS proteomics experiment is mzIdentML. The version 1. 1, considered as the first stable version, was released in 2011  44  and version 1. 2  45  in 2017, adding features for workflows such as de novo sequencing, cross-linking, proteogenomics approaches and improved encoding of protein inference results. The mzIdentML format is widely implemented in over 35 software tools (https://www. psidev. info/ tools-implementing-mzidentml) and an encouraged (but not required) format at the ProteomeXchange data repositories, since it is one of the standard formats that can be used for performing "Complete" submissions (those where the identification data can be parsed and linked to the mass spectra by the receiving repository).
After some years of use, it was concluded by PSI working groups that while the attempt to support both proteomics and metabolomics in the same format was a noble idea, the result was a format that did not serve either data type as well as desired. As a result, mzTab-M 50 was redesigned as a format that would fix some perceived design issues and support only metabolomics. Its data model is backed by a JSON-based schema, supporting serialization into a tab-separated main storage format or JSON as a transfer format. Since then, it has been adopted by a number of metabolomics and lipidomics software packages and repositories (https://github. com/ HUPO-PSI/mzTab#current-activities-and-software-support). Additionally, similarly to mzIdentML, mzTab can also be used for performing "Complete" submissions to ProteomeXchange data repositories.
Unfortunately, the formats have not been widely adopted so far. Most people use their own variation of the original BED format for representing peptide coordinates in a genome context, by using a small number of columns. Additionally, there is not a perceived need yet to use the more verbose proBAM format. In our view, by using these formats, proteogenomics studies would benefit from a greater standardization in data representation. The added advantage is that most genomics viewers developed would be able to visualize these files. PEFF. The PSI Extended FASTA Format 52 (PEFF) was developed as a format that is broadly compatible with the ubiquitous FASTA format, but defines mechanisms for filelevel metadata, multiple sequence collections within a file, collection-level metadata, and how a wide variety of additional information can be encoded on a per-sequence basis.
Whereas the description lines in FASTA files are free form and vary widely based on the data provider, the format of description lines for PEFF files are defined in the specification and can be extended with controlled vocabulary terms. This allows PEFF files to encode proteins and their modifications, such as posttranslational modifications (PTMs), protein processing such as signal peptides, and sequence variants. Implementations of PEFF support in Comet  53  enables transparent searching for known PTMs and sequence variants. 54 Although it was not originally designed with this use case in mind, PEFF can also be used to represent proteoforms, as detailed in section 3. 4 of the PEFF specification. ProForma 2. 0. The Consortium for Top-Down Proteomics (CTDP) defined the initial 1. 0 ProForma notation  55  to encode exact proteoforms with all applicable PTMs on a specific sequence.
Often such spectra are published as figures in journal articles or may appear in Supporting Information as static figures that prevent close scrutiny. Additionally, in the context of FAIR data, it is recommended to have unique identifiers for different types of entities (in this case mass spectra) in public data repositories. While not a file format in itself, the PSI has defined the USI  57  as a multipart key that can be copy-pasted into manuscripts or other conversations about important spectra in order to facilitate the identification and retrieval of specific spectra and PSMs. USIs currently identify spectra that have been deposited into one of the ProteomeXchange public data repositories, although extensions are underway to support USIs for spectra in spectral libraries, both for proteomics as well as metabolomics.
Related Formats Although not officially ratified formats of the PSI, there are a few formats that are highly related to the efforts of the PSI and ProteomeXchange, and will be briefly described here. ProteomeXchange XML (PX XML). The ProteomeXchange (PX) Consortium  [3] [4] [5]  has been receiving and making public proteomics data sets from the community since 2012, and PX members are highly active in the PSI. The data sets themselves always remain at the receiving repository for a submission, but the most important metadata about each data set is transmitted from the receiving repository to Proteome-Central (http://proteomecentral. proteomexchange. org/) whenever a data set is made public. Searches involving public data sets in any ProteomeXchange resource can then be enabled. The common format for this is PX XML (current version is 1.
55 IDF is quite analogous to the PX XML format, although it is less structured and is not as rich in information as PX XML. PX XML files can be easily converted by the ProteomeXchange resources into IDF with some loss of information. SDRF-Proteomics files provide the previously missing�and much needed�mechanism for sample-specific annotations with CV terms, and encode the links from those samples to the submitted data files. Sample attributes are encoded in the columns of the files, where the column definitions are required to be CV terms and the data values are either CV terms or plain scalar values when CV terms are not appropriate. Several ProteomeXchange repositories now accept and process SDRF-Proteomics files upon submission of data sets, and the GitHub repository at https://github. com/bigbio/proteomicsmetadata-standard provides a mechanism for anyone in the community to manually curate and generate SDRF-Proteomics files for ProteomeXchange data sets that were previously released.
Due to the extensive software development that must still take place, dedicated funding will likely be required to complete the design and achieve implementations at all ProteomeXchange resources. ProXI is the mechanism that drives the multirepository USI lookup and display mechanism at Proteome-Central described above. ProXI uses the OpenAPI 3. 0 platform for designing end points with a JSON communication format. The data set end point is modeled after the PX XML schema, and the spectrum end point is modeled using the mzSpecLib schema described above. The current state of the ProXI schema definition is found at https://github. com/HUPO-PSI/ proxi-schemas. PTM Site Formats. As part of "PTMeXchange", a project funded by the United Kingdom Biotechnology and Biological Sciences Research Council (BBSRC) and the United States National Science Foundation (NSF) to improve sharing and deposition of high-quality sets of PTMs, a set of formats to encode PTM results are being developed.
The guidelines provide recommendations for data producers on how to describe the results of their IDPrelated experiments, for biocurators on how to annotate experimental data in manually curated community resources, and for database developers on how to disseminate the data. Information about the protein region, the structural state, and the experimental and computational approaches is required to create a MIADE-compliant description of an IDP experiment. The PSI-IDP working group drafted and submitted for publication an article 72 describing the MIADE guidelines and will submit the full specification to the PSI document process as well. The PSI-IDP working group also implemented these guidelines in DisProt, a manually curated resource of intrinsically disordered proteins and regions from the literature.