A computer-implemented method for predicting likelihoods of splice sites in pre-mRNA genomic sequences, the computer-implemented method including: training an atrous convolutional neural network (ACNN) on training examples of pre-mRNA nucleotide sequences, including at least 50000 training examples of donor splice sites, at least 50000 training examples of acceptor splice sites, and at least 100000 training examples of non-splicing sites, wherein the training includes: inputting one-hot encoded training examples of the pre-mRNA nucleotide sequences, wherein each training example is a target nucleotide sequence comprising at least one target nucleotide flanked by at least 20 nucleotides on each side, wherein the target nucleotide sequence is further flanked by 200 upstream context nucleotides and 200 downstream context nucleotides; and adjusting, by backward propagation, parameters of filters in the ACNN to predict scores for a likelihood that each target nucleotide in the target nucleotide sequence is a donor splice site, an acceptor splice site, or a non-splicing site; whereby the trained ACNN is configured to evaluate a one-hot encoded pre-mRNA nucleotide sequence as input to the ACNN, that has an input target nucleotide sequence flanked by at least 200 upstream context nucleotides and at least 200 downstream context nucleotides; and based on the evaluation of the input pre-mRNA nucleotide sequence, producing, as output scores for the likelihood that each target nucleotide in the input target nucleotide sequence is a donor splice site, an acceptor splice site, or a non-splicing site. training an atrous convolutional neural network (ACNN) on training examples of pre-mRNA nucleotide sequences, including at least 50000 training examples of donor splice sites, at least 50000 training examples of acceptor splice sites, and at least 100000 training examples of non-splicing sites, wherein the training includes: inputting one-hot encoded training examples of the pre-mRNA nucleotide sequences, wherein each training example is a target nucleotide sequence comprising at least one target nucleotide flanked by at least 20 nucleotides on each side, wherein the target nucleotide sequence is further flanked by 200 upstream context nucleotides and 200 downstream context nucleotides; and adjusting, by backward propagation, parameters of filters in the ACNN to predict scores for a likelihood that each target nucleotide in the target nucleotide sequence is a donor splice site, an acceptor splice site, or a non-splicing site; inputting one-hot encoded training examples of the pre-mRNA nucleotide sequences, wherein each training example is a target nucleotide sequence comprising at least one target nucleotide flanked by at least 20 nucleotides on each side, wherein the target nucleotide sequence is further flanked by 200 upstream context nucleotides and 200 downstream context nucleotides; and adjusting, by backward propagation, parameters of filters in the ACNN to predict scores for a likelihood that each target nucleotide in the target nucleotide sequence is a donor splice site, an acceptor splice site, or a non-splicing site; whereby the trained ACNN is configured to evaluate a one-hot encoded pre-mRNA nucleotide sequence as input to the ACNN, that has an input target nucleotide sequence flanked by at least 200 upstream context nucleotides and at least 200 downstream context nucleotides; and based on the evaluation of the input pre-mRNA nucleotide sequence, producing, as output scores for the likelihood that each target nucleotide in the input target nucleotide sequence is a donor splice site, an acceptor splice site, or a non-splicing site. <EOS>