Curated catalog of worldwide biological databases to provide landscape of biological databases throughout the world and enable easy retrieval and access to specific collection of databases of interest. Catalog of worldwide biological databases as well as their curated meta information and derived statistics.

Please cite the following paper when using this dataset: N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2

Abstract The world is currently facing an outbreak of the monkeypox virus, and confirmed cases have been reported from 28 countries. Following a recent “emergency meeting”, the World Health Organization is considering whether the outbreak should be assessed as a “potential public health emergency of international concern”, as was done for the COVID-19 and Ebola outbreaks in the past. During this time, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, a dataset of Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

Data Description The dataset consists of a total of 102,452 tweet IDs of the same number of tweets about monkeypox that were posted on Twitter from 7th May 2022 to 26th June 2022 (the most recent date at the time of dataset upload). The Tweet IDs are presented in 5 different files based on the timelines of the associated tweets. The following are the details of these dataset files

Filename: TweetIDs_Part1.txt (No. of Tweet IDs: 13926, Date Range of the associated Tweet IDs: May 7, 2022 to May 21, 2022) Filename: TweetIDs_Part2.txt (No. of Tweet IDs: 17705, Date Range of the associated Tweet IDs: May 21, 2022 to May 27, 2022) Filename: TweetIDs_Part3.txt (No. of Tweet IDs: 17585, Date Range of the associated Tweet IDs: May 27, 2022 to June 5, 2022) Filename: TweetIDs_Part4.txt (No. of Tweet IDs: 19718, Date Range of the associated Tweet IDs: June 5, 2022 to June 11, 2022) Filename: TweetIDs_Part5.txt (No. of Tweet IDs: 33518, Date Range of the associated Tweet IDs: June 12, 2022 to June 26, 2022)

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used.

Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012. We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers. We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status. Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies. We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.

Code Availability in the Journal of the American Statistical Association.

Databases that represent sets of pre-compiled information on biological relationships and associations, interactions and facts which have been extracted from the biomedical literature using Ariadne's MedScan technology. ResNet databases store information harvested from the entire PubMed in a formal structure that allows searching, retrieval and updating by Pathway Studio user. ResNet is seamlessly installed when Pathway Studio is installed. There are several available ResNet databases: *ResNet Mammalian Database includes data for Human, Rat, and Mouse *ResNet Plant Database has data on Arabidopsis, Rice and several other plants. Features of ResNet: *All extracted relations have linked access to the original article or abstract *Synonyms and homologs are included to maintain gene identity and to obviate redundancy in search results *Users can update ResNet as often as required using the MedScan technology built into all Ariadne products *Updates are made available by Ariadne every quarter To purchase Pathway Studio software with ResNet database, for information, or to schedule a web demonstration, call our sales department at (240) 453-6272, or (866) 340-5040 (toll free)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Maintains and provides archival, retrieval and analytical resources for biological information. Central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: DDBJ Omics Archive and BioProject. DOR is archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides organizational framework to access metadata about research projects and data from projects that are deposited into different databases.

Open Access and Open Data/Code Policies 2012.

To enable the identification of mutated peptide sequences in complex biological samples, in this work, two novel cancer- and disease-related protein databases with mutation information collected from several public resources such as COSMIC, IARC P53, OMIM, and UniProtKB were developed. In-house developed Perl scripts were used to search and process the data and to translate each gene-level mutation into a mutated peptide sequence. The cancer and disease mutation databases comprise a total of 872 125 and 27 148 peptide entries from 25 642 and 2913 proteins, respectively. A description line for each entry provides the parent protein ID and name, the cDNA- and protein-level mutation site and type, the originating database, and the disease or cancer tissue type and corresponding hits. The two databases are FASTA-formatted to enable data retrieval by commonly used tandem MS search engines. While the largest number of mutations were encountered for the amino acids A/D/E/G/L/P/R/S, the global mutation profiles replicate closely the outcome of the 1000 Genomes Project aimed at cataloguing natural mutations in the human population. The affected proteins were primarily involved in transcription regulation, splicing, protein synthesis/folding/binding, redox/energy production, adhesion/motility, and to some extent in DNA damage repair and signaling. The applicability of the database to identifying the presence of mutated peptides was investigated with MCF-7 breast cancer cell extracts.

Net Changes in Journal Policy Classifications from 2011 to 2012.

Journal Review and Hosting Policies, 2012.

The EBI is a centre for research and services in bioinformatics. The Institute manages databases of biological data including nucleic acid, protein sequences and macromolecular structures. As we move towards understanding biology at the systems level, access to large data sets of many different types has become crucial. Technologies such as genome-sequencing, microarrays, proteomics and structural genomics have provided 'parts lists' for many living organisms, and researchers are now focusing on how the individual components fit together to build systems. The hope is that scientists will be able to translate their new insights into improving the quality of life for everyone. However, the high-throughput revolution also threatens to drown us in data. There is an ongoing, and growing, need to collect, store and curate all this information in ways that allow its efficient retrieval and exploitation. The European Bioinformatics Institute is one of the few places in the world that has the resources and expertise to fulfil this important task.

Publishing Houses for Journal Titles.

Neocryptolepine is a natural alkaloid isolated from the African climbing plant Paeonia lactiflora, belonging to the indole quinoline alkaloid class. This compound has become a natural precursor widely studied by medicinal chemists due to its diverse biological activities, especially its potential applications in anti-tumor, anti-inflammatory, anti malaria and other fields. As a natural product with multiple biological activities,Neocryptolepine has great potential in cancer treatment research. Through in-depth research and development of the Neocryptolepine, it may provide new treatment options for cancer patients in the future.Cancer, as a global health challenge, has long plagued the medical community and patients. It is a disease caused by the unlimited proliferation, invasion, and metastasis of abnormal cells, which can affect any part of the human body. With the change of lifestyle, the aggravation of environmental pollution and the trend of aging population, the incidence rate of cancer has increased year by year and has become the second leading cause of death in the world. Despite its enormous potential in cancer treatment, the diversity, mechanisms, and unknown targets of action make it extremely challenging to obtain Neocryptolepine anti-cancer pathways from it. In addition, it is difficult to search for systematic information on anti-cancer Neocryptolepine from a large amount of information such as the internet. Neocryptolepine derivatives, as a natural compound, have shown great potential and diversity in cancer treatment. Despite facing challenges in screening and utilization, they remain important resources for drug development.In order to construct the NDADS database, authoritative literature search websites such as Pubmed and Google Scholar were used to systematically collect key information on the generic name, anti-tumor activity, cancer type, mechanism of action, and targets of Neocryptolepine and its derivatives using keywords such as Neocryptolepine, Cancer, and Target. On this basis, all data were integrated and included in the data of 85 Neocryptolepine derivatives in the laboratory, ultimately forming a database containing information on 203 anti-tumor compounds derived from Neocryptolepine derivatives. In order to integrate and evaluate numerous research resources and results, the Neocryptolepine derivatives anti-tumor database can provide rich retrieval and analysis tools, such as cross database retrieval, citation retrieval, journal retrieval, etc., enabling users to easily search for anti-tumor related information of Neocryptolepine derivatives. Supplement the current inclusion status, covering the names, structures, molecular weights, activities, functions, cancer types, cancer cells, targets/signaling pathways, references, and corresponding website sources of various compounds. This interface supports the query function for the content of the Neocryptolepine derivatives mentioned above. Therefore, the anti-tumor database of the Neocryptolepine derivatives will help to study the potential of Neocryptolepine derivatives in the treatment of cancer from multiple aspects such as activity, structure, method of action, and target, assisting in cancer treatment and improving cancer survival rate.

ISI Classifications Represented in the Journal Titles.

Classification of Journal Policies.

To enable the identification of mutated peptide sequences in complex biological samples, in this work, a cancer protein database with mutation information collected from several public resources such as COSMIC, IARC P53, OMIM and UniProtKB, was developed. In-house developed Perl-scripts were used to search and process the data, and to translate each gene-level mutation into a mutated peptide sequence. The cancer mutation database comprises a total of 872,125 peptide entries from 25,642 protein IDs. A description line for each entry provides the parent protein ID and name, the cDNA- and protein-level mutation site and type, the originating database, and the cancer tissue type and corresponding hits. The database is FASTA formatted to enable data retrieval by commonly used tandem MS search engines.