The current coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global outbreak of a disease from a new coronavirus. Several databases have been published on this pandemic, but the research community still needs an easy way to get comprehensive information on COVID-19. COVID-19 pandemic database (CO-19 PDB) aims to provide wonderful insights for COVID-19 researchers with the well-gathered of all the COVID-19 data to one platform, which is a global challenge for the research community these days. We gathered 59 updated databases since December-2019 until May 2021 and divided them into six categories: digital image database, genomic database, literature database, visualization tools database, chemical structure database, and social science database. These categories focus on taking number of functions from the images, information from gene sequences, updates from relevant papers, essays, reports, articles, and books, the data or information in the form of maps, graphs, and charts, information of bonds between atoms, and updates about events of the physical and social environment, respectively. Users can search the information of interest in two ways including typing the name of the database in the search bar or by clicking the right category directly. Computer languages such as CSS, PHP, HTML, Java, etc. are utilized to construct CO-19 PDB. This article attempts to compile up-to-date appropriate COVID-19 datasets and resources that have not been compiled and given in such an accessible and user-friendly manner. As a result, the CO-19 PDB offers extensive open data sharing for both worldwide research communities and local people. Further, we have planned future development of new features, that will be awesome for future study.

Background: The advancement of cancer research has been facilitated through freely available cancer literature, databases, and tools. The age of genomics and big data has given rise to the need for cooperation and data sharing in order to make efficient use of this new information in the COVID-19 pandemic. Although there are many databases for cancer research, their access is not easy owing to different ways of processing and managing the data. There is an absence of a unified platform to manage all of them in a transparent and more comprehensible way. Objective: In this study, an improved integrated cancer research database and platform is provided to facilitate a deeper statistical insight into the correlation between cancer and the COVID-19 pandemic, unifying the collection of almost all previous published cancer databases and defining a model web database for cancer research, and scoring databases on the basis of the variety types of cancer, sample size, completeness of omics results, and user interface. Methods: Databases examined and integrated include the Data Portal database, Genomic database, Proteomic database, Expression database, Gene database, and Mutation database; and it is expected that this launch will sort, save, advance the understanding and encourage the use of these resources in the cancer research environment. Results: To make it easy to search valuable information, 85 cancer databases are provided in the form of a table, and a database of databases named the Cancer Research Database (CRDB) has been built and presented herein. Furthermore, the CRDB has been herein equipped with unique navigation tools in order to be explored by three methods; that is, any single database can be browsed by typing the name in the given search bar, while all categories can be browsed by clicking on the name of the category or image expression icon, thus serving as a facility that could provide all the category databases on a single click. Conclusions: The computational platform (PHP, HTML, CSS, and MySQL) used to build CRDB for the cancer scientific community can be freely investigated and browsed on the internet and is planned to be updated in a timely manner. In addition, based on the proposed platform, the status and diagnoses statistics of cancer during the COVID-19 pandemic have been thoroughly investigated herein using CRDB, thus providing an easy-to-manage, understandable framework that mines knowledge for future researchers.

Background: The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive grow... Lay abstract We have compiled the most recent collection of human research datasets into six categories – DNA database, RNA database, protein database, expression database, pathway database and dis...

Aim: Head and Neck squamous cell carcinoma (HNSCC) is the second most prevalent cancer in Pakistan. Methods: Gene expression data from TCGA and GETx for normal genes to analyze Differentially Expressed Genes (DEGs). Data was further investigated using the Enrichr tool to perform Gene Ontology (GO). Results: Our analysis identified most significantly differentially expressed genes and explored their established cellular functions as well as their potential involvement in tumor development. We found that the highly expressed Keratin family and S100A9 genes. The under-expressed genes KRT4 and KRT13 provide instructions for the production of keratin proteins. Conclusion: Our study suggests that factors such as poor oral hygiene and smokeless tobacco can result in oral stress and cellular damage and cause cancer.

Clinical judgement and suspicion of influenza based on signs and symptoms of influenza-like illness and severe acute respiratory illness are critical for better patient outcome. Whether clinical characteristics of patients are associated with the development of acute respiratory distress syndrome and PCR positivity of samples was the aim of this study. We included all patients (n=37) presenting with influenza like illness (ILI) or severe acute respiratory illness (SARI) to a tertiary care hospital in northwest Pakistan during December 2015 until the end of January 2016. Each patient was assessed for signs and symptoms, clinical features, treatment, complications and outcome of ILI and SARI. Throat or nasopharyngeal swabs were obtained from 36 patient and analyzed for the presence of Influenza virus by quantitative PCR. Patients presenting with ILI or SARI were febrile (p<0.001, one sample t-test), significantly tachypneic (p<0.001) and had critically lower oxygen saturation (p<0.001). Nasal congestion at presentation (p=0.006, chi-square test for association) and infiltrates on chest radiographs (p=0.025) were significantly associated with acute respiratory distress syndrome. Likelihood of the occurrence of ARDS was significantly increased with decrease in oxygen saturation (Odds ratio; 0.75, 95% CI; 0.46, 1.21, p=0.048) and marginally significantly increased in lower age (Odds ratio; 0.82, 95% CI; 0.58, 1.15, p=0.055) and higher white cell count (Odds ratio; 1.001, 95% CI; 0.99, 1.002, p=0.054). The presence of Influenza type A/H1N1pdm09 strains was confirmed in 7/11 patients. However no significant difference was observed in the clinical features and complications of PCR positive and negative patients. Clinical signs and symptoms of influenza-like illness or severe acute respiratory illness significantly predict the development of complications irrespective of the positivity or negativity of laboratory qPCR reports.