![]() ![]() Transient protein-protein interface prediction: datasets, features, algorithms, and the RAD-T predictor. J., Liu S., Aumentado-Armstrong T., Istrate B., Cernek P. Plausible blockers of Spike RBD in SARS-CoV-2-molecular design and underlying interaction dynamics from high-level structural descriptors. 10.1093/bioinformatics/btv639īasu S., Chakravarty D., Bhattacharyya D., Saha P., Patra H. Gapped sequence alignment using artificial neural networks: application to the MHC class I system. NGS SARS-CoV-2 immunogenomics surveillance variants.Ĭopyright © 2022 De Marco, Veneziano, Massacci, Pallocca, Marascio, Quirino, Barreca, Giancotti, Gallo, Lamberti, Quaresima, Santamaria, Biamonte, Scicchitano, Trecarichi, Russo, Torella, Quattrone, Torti, Matera, De Filippo, Costanzo and Viglietto.Īndreatta M., Nielsen M. In conclusion, we report on the results of SARS-CoV-2 surveillance in Regione Calabria in the period between March 2021 and February 2022, identified variants that were enriched mainly in Calabria, and predicted the effects of identified mutations on host immune response. Prediction analysis of the effects of mutations on the immune response (i.e., binding to class I MHC and/or recognition of T cells) indicated that T29I in B.1 variant A701S in Alpha variant and T19R in Delta variant were predicted to impair binding to class I MHC whereas the mutations A67S identified in Alpha E484K identified in Gamma and E156G and ΔF157/R158 identified in Delta were predicted to impair recognition by T cells. Among the genomes identified in this study, some were distributed all over Europe (B1_S477N, Alpha_L5F, Delta_T95, Delta_G181V, and Delta_A222V), some were distributed in the majority of Italian regions (B1_S477N, B1_Q675H, Delta_T95I and Delta_A222V), and some were present mainly in Calabria (B1_S477N_T29I, B1_S477N_T29I_E484Q, Alpha_A67S, Alpha_A701S, and Alpha_T724I). No patient carrying Beta, Iota, Mu, or Eta variants was identified in this survey. As of January 2022, Omicron emerged and took over Delta (72 and 28%, respectively). In August 2021, Delta became the only circulating variant until the end of December 2021. Our results indicated that B.1 and Alpha were the only circulating lineages in Calabria in March 2021 while Alpha remained the most common variant between April 2021 and May 2021 (90 and 73%, respectively), we observed a concomitant decrease in B.1 cases and appearance of Gamma cases (6 and 21%, respectively) C.36.3 and Delta appeared in June 2021 (6 and 3%, respectively) Delta became dominant in July 2021 while Alpha continued to reduce (46 and 48%, respectively). We have identified circulating VOCs by Sanger sequencing of the S gene and defined their genotypes by whole-genome NGS sequencing of 157 representative isolates. To this study, we have sequenced RNA from 609 isolates. No tenure-track academic position is linked to this job offer.In this study, we report on the results of SARS-CoV-2 surveillance performed in an area of Southern Italy for 12 months (from March 2021 to February 2022). We offer flexible working time and a combination of local/remote working schemes. ![]() Payscale at postdoc level depending on the candidate’s experience. Proved publication track record (minimum Scopus H-index equal to 7) PhD in Biomedical Engineering, Computer Science, Computer Vision, Data Science, Medical Physics, or related field, with emphasis on medical image analysis and artificial intelligence (both machine learning and deep learning) The project, in collaboration with the European Institute of Oncology (Milan) and Azienda Ospedaliero-Universitaria Cagliari, aims at using CT scans and artificial intelligence to predict the therapeutic outcomes (both pharmacological and surgical) for gynecological cancer patients. We are looking for a motivated person to work as a post-doc on a medical image analysis project at Magna Graecia University of Catanzaro, Italy. Artificial intelligence for prediction of gynecological cancer outcomeĮmail Address Closing date: March 10th, 2023 ![]() Title Post-doc position at Magna Graecia University of Catanzaro, Italy. Organization Magna Graecia University of Catanzaro Artificial intelligence for prediction of gynecological cancer outcome Post-doc position at Magna Graecia University of Catanzaro, Italy. ![]()
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