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Motivation RNA secondary structure plays a vital role in fundamental cellular processes, and identification of RNA secondary structure is a key step to understand RNA functions. Recently, a few experimental methods were developed to profile genome-wide RNA secondary structure, i.e. the pairing probability of each nucleotide, through high-throughput sequencing techniques. However, these high-throughput methods have low precision and can’t cover all nucleotides due to limited sequencing coverage. Results Here we have developed a new method for the prediction of genome-wide RNA secondary structure profile from RNA sequence based on the extreme Gradient Boosting technique. The method achieves predictions with areas under the receiver operating characteristic curve (AUC) greater than 0.9 on three different datasets, and AUC of 0.888 by an independent test on the recently released Zika virus data. These AUCs are consistently >5 % greater than the ones by the CROSS method recently developed based on a shallow neural network. Further analysis on the 1000 Genome Project data showed that our predicted unpaired probabilities are highly correlated (>0.8) with the minor allele frequencies at synonymous, non-synonymous mutations, and mutations in untranslated region, which were higher than those generated by RNAplfold. Moreover, the prediction over all human mRNA indicated a consistent result with previous observation that there is a periodic distribution of unpaired probability on codons. The accurate prediction by our method indicates that such model trained on genome-wide experimental data might be an alternative for analytical methods. Availability The GRASP is available for academic use at https//github.com/sysu-yanglab/GRASP. Supplementary information Supplementary data are available online.Motivation Exposure to pesticides may lead to adverse health effects in human populations, in particular vulnerable groups. The main long-term health concerns are neurodevelopmental disorders, carcinogenicity as well as endocrine disruption possibly leading to reproductive and metabolic disorders. Adverse Outcome Pathways (AOP) consist in linear representations of mechanistic perturbations at different levels of the biological organization. Although AOPs are chemical-agnostic, they can provide a better understanding of the Mode of Action of pesticides and can support a rational identification of effect markers. NMUchemical Results With the increasing amount of scientific literature and the development of biological databases, investigation of putative links between pesticides, from various chemical groups, and AOPs using the biological events present in the AOP-Wiki database is now feasible. To identify co-occurrence between a specific pesticide and a biological event in scientific abstracts from the PubMed database, we used an updated version of the artificial intelligence-based AOP-helpFinder tool. This allowed us to decipher multiple links between the studied substances and molecular initiating events (MIE), key events (KE) and adverse outcomes (AO). These results were collected, structured and presented in a web application named AOP4EUpest that can support regulatory assessment of the prioritized pesticides, and trigger new epidemiological and experimental studies. Availability and implementation http//www.biomedicale.parisdescartes.fr/aop4EUpest/home.php. Supplementary information Supplementary data and information are available at Bioinformatics online and on GitHub https//github.com/jornod/aophelpfinder2 .Summary AlphaFamImpute is an imputation package for calling, phasing, and imputing genome-wide genotypes in outbred full-sib families from single nucleotide polymorphism (SNP) array and genotype-by-sequencing (GBS) data. GBS data is increasingly being used to genotype individuals, especially when SNP arrays do not exist for a population of interest. Low-coverage GBS produces data with a large number of missing or incorrect naïve genotype calls, which can be improved by identifying shared haplotype segments between full-sib individuals. Here we present AlphaFamImpute, an algorithm specifically designed to exploit the genetic structure of full-sib families. It performs imputation using a two-step approach. In the first step it phases and imputes parental genotypes based on the segregation states of their offspring (that is, which pair of parental haplotypes the offspring inherited). In the second step it phases and imputes the offspring genotypes by detecting which haplotype segments the offspring inherited from their parents. With a series of simulations we find that AlphaFamImpute obtains high accuracy genotypes, even when the parents are not genotyped and individuals are sequenced at less than 1x coverage. Availability and implementation AlphaFamImpute is available as a Python package from the AlphaGenes website, http//www.AlphaGenes.roslin.ed.ac.uk/AlphaFamImpute. Supplementary information A complete description of the methods is available in the supplementary information.Efforts to develop a male contraceptive method beyond condoms and vasectomy have been on-going for nearly 70 years. During this time there have been ebbs and modest flows of resources available to support product development, but not at a level sufficient to carry research efforts through to market. The small community of researchers that have continued to pursue the development of male contraceptives is comprised of dedicated scientists who have a great deal of knowledge and experience to offer. While collaboration has been an organic outcome of limited resources, competing research objectives and geographically diverse locations have made consistent and sustained progress challenging, particularly for those working in the earliest stages of developing non-hormonal, reversible male contraceptive methods. While the past decade has seen an increase in funding to the field, the levels are still modest when placed in the context of actual costs to bring products to market. In addition, there are challenges still to be identified given that there is no regulatory precedent for these products. These challenges present an excellent use case for the application of design-thinking, or human centered design, as a means of generating novel solutions. By engaging those with deep technical expertise in the field of male contraception as well as thought leaders from other fields of practice, design-thinking offers an opportunity to identify potential strategies, including non-traditional approaches, capable of driving the product development process forward, in a faster and more efficient manner.