Fallmann, J. | bioRxiv Science

bioRxiv2022

Tailored machine learning models for functional RNA detection in genome-wide screens

The in silico prediction of non-coding and protein-coding genetic loci is an area of research that has gathered large attention in the field of comparative genomics. In the last decade, much effort has been made to investigate numerous properties of nucleotide sequences that hint at their biological role in the cell. We present here a software framework for the alignment-based training, evaluation and application of machine learning models with user-defined parameters. Instead of focusing on the one-size-fits-all approach of pervasive in silico annotation pipelines, we offer a framework for the structured generation and evaluation of models based on arbitrary features and input data, focusing on stable and explainable results. Furthermore, we showcase the usage of our software package in a full-genome screen of Drosophila melanogaster and evaluate our results against the well-known but much less flexible program RNAz.

bioinformatics↗

bioRxiv2020

Supervised and Unsupervised Classification of lncRNA Subtypes

Many small nucleolar RNAs and many of the hairpin precursors of miRNAs are processed from long non-protein-coding (lncRNA) host genes. In contrast to their highly conserved and heavily structured payload, the host genes feature poorly conserved sequences. Nevertheless there is mounting evidence that the host genes have biological functions. No obvious connections between the function of the host genes and the function of their payloads have been reported. Here we inverstigate whether there is an association of host gene function or mechanisms with the type of payload. To assess this hypothesis we test whether the miRNA host genes (MIRHGs), snoRNA host genes (SNHGs), and other lncRNAs host genes can be distinguished based on sequence and structure features. A positive answer would imply a correlation between host genes and their payload. While the three classes can be distinguished reliably when the classifier is allowed to extract features from the payloads, this is no longer the case when only sequence and structure of parts of the host gene distal from the snoRNAs or miRNA payload is used for classification. Our data indicate that the functions of MIRHGs and SNHGs are largely independent of the functions of their payloads. Furthermore, there is no evidence that the MIRHGs and SNHGs form coherent classes of long non-coding RNAs distinguished by features other than their payloads.

bioinformatics↗