VCF files containing filtered mutated sites in SARS-CoV-2 genomes obtained from GISAID EpiCoV and submitted from the UK and the US, separated by individual mutations. The columns correspond to viral genome accession ID, nucleotide position in the genome, mutation ID (left blank in all rows), reference nucleotide, identified mutation, quality, filter, and information columns (all left blank), format (GT in all rows), column corresponding to reference genome (all 0, referring to reference nucleotide column), and columns corresponding to isolate genomes, with each row identifying the nucleotide in the POS column, and whether it is non-mutant (0), or the mutant indicated in the identified mutation column (1). The files is tab delimited, with the UK file having 12696 rows including the names, and 18135 columns, and the US file having 15588 rows including the names, and 16277 columns.

The file was generated to test the hypothesis whether the different SARS-CoV-2 genes or protein coding regions are positively or negatively selected differently between 14408C>T / 23403A>G double mutants and double wildtype isolates, using mutation rate models, and whether regional distributions affect the mutation rates. Our findings have shown that the RdRp coding region and the S gene show the highest amount of selection across viral generations, and that different countries can affect the synonymous and nonsynonymous mutation rates for individual genes.

Contains most of the necessary files for running the analysis and plotting scripts.Please check analysis-plotting in https://github.com/josegcpa/wbs-prediction for more details.

Portuguese National Registry on low weight newborns between 2013 and 2018, made available for research purposes. Dataset is composed of 3823 unique entries registering birthweight, biological sex of the infant (1-Male; 2-Female), CRIB score (0-21) and survival (0-Survival; 1-Death).

Bioenergetics data ( DEL2G ) of interaction between D614G mutants vs N501Y mutants are statistically analysed to find out the correlation study .

Explore the progression of average salaries for graduates in Health Science In Biostatistics - Bioinformatics Track from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Health Science In Biostatistics - Bioinformatics Track relative to other fields. This data is essential for students assessing the return on investment of their education in Health Science In Biostatistics - Bioinformatics Track, providing a clear picture of financial prospects post-graduation.

BackgroundDuring mesenchymal stem cell (MSC) conversion into adipocytes, the adipogenic cocktail consisting of insulin, dexamethasone, indomethacin and 3-isobutyl-1-methylxanthine not only induces adipogenic-specific but also genes for non-adipogenic processes. Therefore, not all significantly expressed genes represent adipogenic-specific marker genes. So, our aim was to filter only adipogenic-specific out of all expressed genes. We hypothesize that exclusively adipogenic-specific genes change their expression during adipogenesis, and reverse during dedifferentiation. Thus, MSC were adipogenic differentiated and dedifferentiated.ResultsAdipogenesis and reverse adipogenesis was verified by Oil Red O staining and expression of PPARG and FABP4. Based on GeneChips, 991 genes were differentially expressed during adipogenesis and grouped in 4 clusters. According to bioinformatic analysis the relevance of genes with adipogenic-linked biological annotations, expression sites, molecular functions, signaling pathways and transcription factor binding sites was high in cluster 1, including all prominent adipogenic genes like ADIPOQ, C/EBPA, LPL, PPARG and FABP4, moderate in clusters 2–3, and negligible in cluster 4. During reversed adipogenesis, only 782 expressed genes (clusters 1–3) were reverted, including 597 genes not reported for adipogenesis before. We identified APCDD1, CHI3L1, RARRES1 and SEMA3G as potential adipogenic-specific genes.ConclusionThe model system of adipogenesis linked to reverse adipogenesis allowed the filtration of 782 adipogenic-specific genes out of total 991 significantly expressed genes. Database analysis of adipogenic-specific biological annotations, transcription factors and signaling pathways further validated and valued our concept, because most of the filtered 782 genes showed affiliation to adipogenesis. Based on this approach, the selected and filtered genes would be potentially important for characterization of adipogenesis and monitoring of clinical translation for soft-tissue regeneration. Moreover, we report 4 new marker genes.

This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Health Science In Biostatistics - Bioinformatics Track. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Health Science In Biostatistics - Bioinformatics Track. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

dataset referring to

Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design

Lorenzo Bertizzolo¹, Patrick M Bossuyt², Ignacio Atal^{1, 5}, Philippe Ravaud^{1, 3-6}, Agnès Dechartres⁷

¹ INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of therapeutic evaluation of chronic diseases Team (METHODS), Paris, F-75004 France; Paris Descartes University, Sorbonne Paris Cité, France.

² Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Netherlands.

³ Centre d’Épidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP (Assistance Publique des Hôpitaux de Paris), Paris, France.

⁴ Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.

⁵ Cochrane France, Paris, France

⁶ Columbia University, Mailman School of Public Health, Department of Epidemiology, New York, USA

⁷ Sorbonne Université, INSERM, Institut Pierre Louis de Santé Publique, Département Biostatistique, Santé Publique et Information Médicale, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière – Charles Foix, Paris, France

BackgroundClinical progression of colorectal cancers (CRC) may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence.Methodology/Principal FindingsStudies were performed on normal mucosa, adenoma, and carcinoma samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data was generated using two normalization algorithms: MAS5.0 and GCRMA with least-variant set (LVS). The data was evaluated using pair-wise comparisons and data decomposition into singular value decomposition (SVD) modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Expressional profiles obtained in 105 samples of whole tissue sections were used to establish oncogenic signaling alterations in progression of CRC, while those representing 40 microdissected specimens were used to select differences in KEGG pathways between epithelium and mucosa. Based on a consensus of the results obtained by two normalization algorithms, and two probe set sorting criteria, we identified 14 and 17 KEGG signaling and metabolic pathways that are significantly altered between normal and tumor samples and between benign and malignant tumors, respectively. Several of them were also selected from the raw microarray data of 2 recently published studies (GSE4183 and GSE8671).Conclusion/SignificanceAlthough the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results.

This linear chart displays the number of PERM cases filed for graduates in Health Science In Biostatistics - Bioinformatics Track from 2020 to 2023, highlighting the trends and changes in sponsorship over the years. It provides a deep dive into how graduates in this specific major have engaged with potential employers for permanent residency in the U.S., illustrating the major’s effectiveness in connecting students with career opportunities that lead to permanent residency

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2019.Database for those interested in the consequences of Factor VIII genetic variation at the DNA and protein level, it provides access to data on the molecular pathology of haemophilia A. The database presents a review of the structure and function of factor VIII and the molecular genetics of haemophilia A, a real time update of the biostatistics of each parameter in the database, a molecular model of the A1, A2 and A3 domains of the factor VIII protein (based on the crystal structure of caeruloplasmin) and a bulletin board for discussion of issues in the molecular biology of factor VIII. The database is completely updated with easy submission of point mutations, deletions and insertions via e-mail of custom-designed forms. A methods section devoted to mutation detection is available, highlighting issues such as choice of technique and PCR primer sequences. The FVIII structure section now includes a download of a FVIII A domain homology model in Protein Data Bank format and a multiple alignment of the FVIII amino-acid sequences from four species (human, murine, porcine and canine) in addition to the virtual reality simulations, secondary structural data and FVIII animation already available. Finally, to aid navigation across this site, a clickable roadmap of the main features provides easy access to the page desired. Their intention is that continued development and updating of the site shall provide workers in the fields of molecular and structural biology with a one-stop resource site to facilitate FVIII research and education. To submit your mutants to the Haemophilia A Mutation Database email the details. (Refer to Submission Guidelines)