An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks.

Timely and effective use of antimicrobial drugs can improve patient outcomes, as well as help safeguard against resistance development. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently routinely used in clinical diagnostics for rapid species identification. Mining additional data from said spectra in the form of antimicrobial resistance (AMR) profiles is, therefore, highly promising.

CpG Transformer for imputation of single-cell methylomes.

Motivation: The adoption of current single-cell DNA methylation sequencing protocols is hindered by incomplete coverage, outlining the need for effective imputation techniques. The task of imputing single-cell (methylation) data requires models to build an understanding of underlying biological processes.

Results: We adapt the transformer neural network architecture to operate on methylation matrices through combining axial attention with sliding window self-attention.