Dataset Information

Protein segment finder: an online search engine for segment motifs in the PDB.

ABSTRACT: Finding related conformations in the Protein Data Bank (PDB) is essential in many areas of bioscience. To assist this task, we designed a search engine that uses a compact database to quickly identify protein segments obeying a set of primary, secondary and tertiary structure constraints. The database contains information such as amino acid sequence, secondary structure, disulfide bonds, hydrogen bonds and atoms in contact as calculated from all protein structures in the PDB. The search engine parses the database and returns hits that match the queried parameters. The conformation search engine, which is notable for its high speed and interactive feedback, is expected to assist scientists in discovering conformation homologs and predicting protein structure. The engine is publicly available at http://ari.stanford.edu/psf and it will also be used in-house in an automatic mode aimed at discovering new protein motifs.

SUBMITTER: Samson AO

PROVIDER: S-EPMC2686524 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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Protein segment finder: an online search engine for segment motifs in the PDB.

Samson Abraham O AO Levitt Michael M

Nucleic acids research 20081030 Database issue

Finding related conformations in the Protein Data Bank (PDB) is essential in many areas of bioscience. To assist this task, we designed a search engine that uses a compact database to quickly identify protein segments obeying a set of primary, secondary and tertiary structure constraints. The database contains information such as amino acid sequence, secondary structure, disulfide bonds, hydrogen bonds and atoms in contact as calculated from all protein structures in the PDB. The search engine p ...[more]

PMID: 18974183

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Project description:BACKGROUND:The coronavirus disease (COVID-19) is the latest pandemic of the digital age. With the internet harvesting large amounts of data from the general population in real time, public databases such as Google Trends (GT) and the Baidu Index (BI) can be an expedient tool to assist public health efforts. OBJECTIVE:The aim of this study is to apply digital epidemiology to the current COVID-19 pandemic to determine the utility of providing adjunctive epidemiologic information on outbreaks of this disease and evaluate this methodology in the case of future pandemics. METHODS:An epidemiologic time series analysis of online search trends relating to the COVID-19 pandemic was performed from January 9, 2020, to April 6, 2020. BI was used to obtain online search data for China, while GT was used for worldwide data, the countries of Italy and Spain, and the US states of New York and Washington. These data were compared to real-world confirmed cases and deaths of COVID-19. Chronologic patterns were assessed in relation to disease patterns, significant events, and media reports. RESULTS:Worldwide search terms for shortness of breath, anosmia, dysgeusia and ageusia, headache, chest pain, and sneezing had strong correlations (r>0.60, P<.001) to both new daily confirmed cases and deaths from COVID-19. GT COVID-19 (search term) and GT coronavirus (virus) searches predated real-world confirmed cases by 12 days (r=0.85, SD 0.10 and r=0.76, SD 0.09, respectively, P<.001). Searches for symptoms of diarrhea, fever, shortness of breath, cough, nasal obstruction, and rhinorrhea all had a negative lag greater than 1 week compared to new daily cases, while searches for anosmia and dysgeusia peaked worldwide and in China with positive lags of 5 days and 6 weeks, respectively, corresponding with widespread media coverage of these symptoms in COVID-19. CONCLUSIONS:This study demonstrates the utility of digital epidemiology in providing helpful surveillance data of disease outbreaks like COVID-19. Although certain online search trends for this disease were influenced by media coverage, many search terms reflected clinical manifestations of the disease and showed strong correlations with real-world cases and deaths.

Dataset Information

Protein segment finder: an online search engine for segment motifs in the PDB.

Publications

Protein segment finder: an online search engine for segment motifs in the PDB.

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