To make machine-learning analyses in the life sciences more computationally reproducible,
we propose standards based on data, model and code publication, programming best …

Motivation Classification by supervised machine learning greatly facilitates the annotation of
protein characteristics from their primary sequence. However, the feature generation step in …

High throughput gene expression profiling is a powerful approach to generate hypotheses on
the underlying causes of biological function and disease. Yet this approach is limited by its …

Those building predictive models from transcriptomic data are faced with two conflicting
perspectives. The first, based on the inherent high dimensionality of biological systems, …

The value of scientific research can be easier to assess at the collective level than at the level
of individual contributions. Several journal-level and article-level metrics aim to measure …

Background Hetnets, short for “heterogeneous networks,” contain multiple node and relationship
types and offer a way to encode biomedical knowledge. One such example, Hetionet, …

Technologies for quantifying biology have undergone significant advances in the past few
decades, leading to datasets rapidly increasing in size and complexity. At the same time, deep …

Those building predictive models from transcriptomic data are faced with two conflicting
perspectives. The first, based on the inherent high dimensionality of biological systems, …

Background Posthepatectomy liver failure (PHLF) contributes significantly to morbidity and
mortality after liver surgery. Standardized assessment of preoperative liver function is crucial …

… The right of John Heil to be identified as author of this work has been asserted by him in
accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. …