AI Medical Compendium Journal:
BMC biology

Showing 21 to 30 of 32 articles

Systematic prediction of degrons and E3 ubiquitin ligase binding via deep learning.

BMC biology
BACKGROUND: Degrons are short linear motifs, bound by E3 ubiquitin ligase to target protein substrates to be degraded by the ubiquitin-proteasome system. Mutations leading to deregulation of degron functionality disrupt control of protein abundance d...

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants.

BMC biology
BACKGROUND: Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been succe...

A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses.

BMC biology
BACKGROUND: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely ...

Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.

BMC biology
BACKGROUND: Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenes...

Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock.

BMC biology
BACKGROUND: Access to quantitative information is crucial to obtain a deeper understanding of biological systems. In addition to being low-throughput, traditional image-based analysis is mostly limited to error-prone qualitative or semi-quantitative ...

Machine-learning strategies for testing patterns of morphological variation in small samples: sexual dimorphism in gray wolf (Canis lupus) crania.

BMC biology
BACKGROUND: Studies of mammalian sexual dimorphism have traditionally involved the measurement of selected dimensions of particular skeletal elements and use of single data-analysis procedures. Consequently, such studies have been limited by a variet...

Machine learning approaches identify male body size as the most accurate predictor of species richness.

BMC biology
BACKGROUND: A major challenge in biodiversity science is to understand the factors contributing to the variability of species richness -the number of different species in a community or region - among comparable taxonomic lineages. Multiple biotic an...

Joint learning improves protein abundance prediction in cancers.

BMC biology
BACKGROUND: The classic central dogma in biology is the information flow from DNA to mRNA to protein, yet complicated regulatory mechanisms underlying protein translation often lead to weak correlations between mRNA and protein abundances. This is pa...

Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BMC biology
BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is a major challenge of modern genomics, especially for precision medicine. Transcription factor (TF) binding profiles and epigenomic landscapes in refe...

Q&A: Understanding the composition of behavior.

BMC biology
Understanding the brain requires understanding behavior. New machine vision and learning techniques are poised to revolutionize our ability to analyze behaviors exhibited by animals in the laboratory. Here we describe one such method, Motion Sequenci...