AIMC Topic: Deep Learning

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A deep learning method to map tissue architecture.

Nature reviews. Genetics
A new study in describes a computational method named UTAG (unsupervised discovery of tissue architecture with graphs) that aims to identify and quantify higher-level tissue domains from biological images without previous knowledge.

Growing ecosystem of deep learning methods for modeling protein-protein interactions.

Protein engineering, design & selection : PEDS
Numerous cellular functions rely on protein-protein interactions. Efforts to comprehensively characterize them remain challenged however by the diversity of molecular recognition mechanisms employed within the proteome. Deep learning has emerged as a...

Magnetic resonance imaging-based deep learning model to predict multiple firings in double-stapled colorectal anastomosis.

World journal of gastroenterology
BACKGROUND: Multiple linear stapler firings during double stapling technique (DST) after laparoscopic low anterior resection (LAR) are associated with an increased risk of anastomotic leakage (AL). However, it is difficult to predict preoperatively t...

Deep learning-based classifier of diffuse large B-cell lymphoma cell-of-origin with clinical outcome.

Briefings in functional genomics
Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma with poor response to R-CHOP therapy due to remarkable heterogeneity. Based on gene expression, DLBCL cases were divided into two subtypes, i.e. ABC and GCB, where AB...

Integrated mRNA sequence optimization using deep learning.

Briefings in bioinformatics
The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a cri...

Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding.

Briefings in bioinformatics
Anticancer peptides (ACPs) are the types of peptides that have been demonstrated to have anticancer activities. Using ACPs to prevent cancer could be a viable alternative to conventional cancer treatments because they are safer and display higher sel...

RNAdegformer: accurate prediction of mRNA degradation at nucleotide resolution with deep learning.

Briefings in bioinformatics
Messenger RNA-based therapeutics have shown tremendous potential, as demonstrated by the rapid development of messenger RNA based vaccines for COVID-19. Nevertheless, distribution of mRNA vaccines worldwide has been hampered by mRNA's inherent therma...

Tracing human life trajectory using gut microbial communities by context-aware deep learning.

Briefings in bioinformatics
The gut microbial communities are highly plastic throughout life, and the human gut microbial communities show spatial-temporal dynamic patterns at different life stages. However, the underlying association between gut microbial communities and time-...

Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning.

Briefings in bioinformatics
With the improvement of single-cell measurement techniques, there is a growing awareness that individual differences exist among cells, and protein expression distribution can vary across cells in the same tissue or cell line. Pinpointing the protein...