Food Modelling Journal: New open-access venue provides a platform for food scientists | EurekAlert! Science News

“The open-access Food Modelling Journal (FMJ) was launched by the AGINFRA+ community and Pensoft with the aim to encourage food science specialists, agronomists and computer scientists to come together and work on assuring and improving food supply, quality and safety in our globalised and rapidly changing world….

FSK-ML is an open information exchange format that is based on harmonised terms, metadata and controlled vocabulary to harmonise annotations of risk assessment models and that was significantly improved and extended during the AGINFRA+ project.”

A community-maintained standard library of population genetic models | bioRxiv

Abstract:  The explosion in population genomic data demands ever more complex modes of analysis, and increasingly these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to duplication of effort and the possibility for error. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a standard catalog of published simulation models from a wide range of organisms and supports multiple simulation engine backends. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage an even broader community of developers to contribute to this growing resource.

 

 

The Natural Products Atlas: An Open Access Knowledge Base for Microbial Natural Products Discovery | ACS Central Science

Abstract:  Despite rapid evolution in the area of microbial natural products chemistry, there is currently no open access database containing all microbially produced natural product structures. Lack of availability of these data is preventing the implementation of new technologies in natural products science. Specifically, development of new computational strategies for compound characterization and identification are being hampered by the lack of a comprehensive database of known compounds against which to compare experimental data. The creation of an open access, community-maintained database of microbial natural product structures would enable the development of new technologies in natural products discovery and improve the interoperability of existing natural products data resources. However, these data are spread unevenly throughout the historical scientific literature, including both journal articles and international patents. These documents have no standard format, are often not digitized as machine readable text, and are not publicly available. Further, none of these documents have associated structure files (e.g., MOL, InChI, or SMILES), instead containing images of structures. This makes extraction and formatting of relevant natural products data a formidable challenge. Using a combination of manual curation and automated data mining approaches we have created a database of microbial natural products (The Natural Products Atlas, www.npatlas.org) that includes 24?594 compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. This database is accompanied by an interactive web portal that permits searching by structure, substructure, and physical properties. The Web site also provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. These interactive tools offer a powerful knowledge base for natural products discovery with a central interface for structure and property-based searching and presents new viewpoints on structural diversity in natural products. The Natural Products Atlas has been developed under FAIR principles (Findable, Accessible, Interoperable, and Reusable) and is integrated with other emerging natural product databases, including the Minimum Information About a Biosynthetic Gene Cluster (MIBiG) repository, and the Global Natural Products Social Molecular Networking (GNPS) platform. It is designed as a community-supported resource to provide a central repository for known natural product structures from microorganisms and is the first comprehensive, open access resource of this type. It is expected that the Natural Products Atlas will enable the development of new natural products discovery modalities and accelerate the process of structural characterization for complex natural products libraries.

The Natural Products Atlas: An Open Access Knowledge Base for Microbial Natural Products Discovery | ACS Central Science

Abstract:  Despite rapid evolution in the area of microbial natural products chemistry, there is currently no open access database containing all microbially produced natural product structures. Lack of availability of these data is preventing the implementation of new technologies in natural products science. Specifically, development of new computational strategies for compound characterization and identification are being hampered by the lack of a comprehensive database of known compounds against which to compare experimental data. The creation of an open access, community-maintained database of microbial natural product structures would enable the development of new technologies in natural products discovery and improve the interoperability of existing natural products data resources. However, these data are spread unevenly throughout the historical scientific literature, including both journal articles and international patents. These documents have no standard format, are often not digitized as machine readable text, and are not publicly available. Further, none of these documents have associated structure files (e.g., MOL, InChI, or SMILES), instead containing images of structures. This makes extraction and formatting of relevant natural products data a formidable challenge. Using a combination of manual curation and automated data mining approaches we have created a database of microbial natural products (The Natural Products Atlas, www.npatlas.org) that includes 24?594 compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. This database is accompanied by an interactive web portal that permits searching by structure, substructure, and physical properties. The Web site also provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. These interactive tools offer a powerful knowledge base for natural products discovery with a central interface for structure and property-based searching and presents new viewpoints on structural diversity in natural products. The Natural Products Atlas has been developed under FAIR principles (Findable, Accessible, Interoperable, and Reusable) and is integrated with other emerging natural product databases, including the Minimum Information About a Biosynthetic Gene Cluster (MIBiG) repository, and the Global Natural Products Social Molecular Networking (GNPS) platform. It is designed as a community-supported resource to provide a central repository for known natural product structures from microorganisms and is the first comprehensive, open access resource of this type. It is expected that the Natural Products Atlas will enable the development of new natural products discovery modalities and accelerate the process of structural characterization for complex natural products libraries.

Meta-Research: Releasing a preprint is associated with more attention and citations for the peer-reviewed article | eLife

Abstract:  Preprints in biology are becoming more popular, but only a small fraction of the articles published in peer-reviewed journals have previously been released as preprints. To examine whether releasing a preprint on bioRxiv was associated with the attention and citations received by the corresponding peer-reviewed article, we assembled a dataset of 74,239 articles, 5,405 of which had a preprint, published in 39 journals. Using log-linear regression and random-effects meta-analysis, we found that articles with a preprint had, on average, a 49% higher Altmetric Attention Score and 36% more citations than articles without a preprint. These associations were independent of several other article- and author-level variables (such as scientific subfield and number of authors), and were unrelated to journal-level variables such as access model and Impact Factor. This observational study can help researchers and publishers make informed decisions about how to incorporate preprints into their work.

Meta-Research: Releasing a preprint is associated with more attention and citations for the peer-reviewed article | eLife

Abstract:  Preprints in biology are becoming more popular, but only a small fraction of the articles published in peer-reviewed journals have previously been released as preprints. To examine whether releasing a preprint on bioRxiv was associated with the attention and citations received by the corresponding peer-reviewed article, we assembled a dataset of 74,239 articles, 5,405 of which had a preprint, published in 39 journals. Using log-linear regression and random-effects meta-analysis, we found that articles with a preprint had, on average, a 49% higher Altmetric Attention Score and 36% more citations than articles without a preprint. These associations were independent of several other article- and author-level variables (such as scientific subfield and number of authors), and were unrelated to journal-level variables such as access model and Impact Factor. This observational study can help researchers and publishers make informed decisions about how to incorporate preprints into their work.

Are huge genetic databases leaving marginalized people out of their data? | Salon.com

“However, as promising as biobanks might seem, the data may tell only partial or even misleading stories. Criticisms of the project include that the research coming out of the UK Biobank will only benefit certain people, and even then, the usefulness of the health associations found are under question.

Compared to the 2011 UK census, Black, Indian, Pakistani and Chinese participants are all underrepresented in the Biobank by at least one third. David Curtis, at University College London, tested whether this under-representation of ethnic minority groups has any impact on schizophrenia genetics research….”

Are huge genetic databases leaving marginalized people out of their data? | Salon.com

“However, as promising as biobanks might seem, the data may tell only partial or even misleading stories. Criticisms of the project include that the research coming out of the UK Biobank will only benefit certain people, and even then, the usefulness of the health associations found are under question.

Compared to the 2011 UK census, Black, Indian, Pakistani and Chinese participants are all underrepresented in the Biobank by at least one third. David Curtis, at University College London, tested whether this under-representation of ethnic minority groups has any impact on schizophrenia genetics research….”

How to add academic journal articles to PubMed: An overview for publishers

“If you work with journals in the biomedical or life sciences, getting the articles you publish added to PubMed to make them more discoverable is likely one of your top goals. But, you may be wondering how to go about it.

We caught up with PubMed Central (PMC) Program Manager Kathryn Funk to get answers to some of the most common questions that we hear from journal publishers about PubMed and the related literature databases at the National Library of Medicine (NLM), MEDLINE and PMC. Read on to learn more about how the PubMed database works and how to apply to have a journal included in MEDLINE or PMC in order to make its articles searchable via PubMed….”