Organism-specific training improves performance of linear B-cell epitope prediction.

Motivation: In silico identification of linear B-cell epitopes represents an important step in the development of diagnostic tests and vaccine candidates, by providing potential high-probability targets for experimental investigation. Current predictive tools were developed under a generalist approach, training models with heterogeneous datasets to develop predictors that can be deployed for a wide variety of pathogens. However, continuous advances in processing power and the increasing amount of epitope data for a broad range of pathogens indicate that training organism or taxon-specific models may become a feasible alternative, with unexplored potential gains in predictive performance.

Transcriptome of tambaqui Colossoma macropomum during gonad differentiation: Different molecular signals leading to sex identity.

Tambaqui (Colossoma macropomum) is the major native species in Brazilian aquaculture, and we have shown that females exhibit a higher growth compared to males, opening up the possibility for the production of all-female population. To date, there is no information on the sex determination and differentiation molecular mechanisms of tambaqui. In the present study, transcriptome sequencing of juvenile trunks was performed to understand the molecular network involved in the gonadal sex differentiation.