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python3 version of bibus https://sourceforge.net/projects/bibus-biblio/ It is nothing more than "it works on Debian testing (bookworm) AMD64. "

FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (paired-end reads from Illumina NGS platforms like Solexa and HiSeq) from diseased samples. The aims of FusionCatcher are: - very good detection rate for finding candidate fusion genes, - very easy to use (i.e. no a priori knowledge of databases and bioinformatics is needed in order to run FusionCatcher), - very good detection of challenging fusion genes, like for example IGH fusions, CIC fusions, DUX4 fusions, CRLF2 fusions, TCF3 fusions, etc. - to be as automatic as possible (i.e. the FusionCatcher will choose automatically the best parameters in order to find candidate fusion genes, e.g. finding automatically the adapters, building the exon-exon junctions automatically based on the length of the input reads, etc.) while providing the best possible detection rate for finding fusion genes.

Network Visualization is a mature part of computer science that is enjoying a good deal of growth, partially fueled by Bioinformatics. Network is a synonym for Graph, and both refer to a collection of nodes and edges.