AI Medical Compendium Journal:
Briefings in functional genomics

Showing 31 to 39 of 39 articles

BioDKG-DDI: predicting drug-drug interactions based on drug knowledge graph fusing biochemical information.

Briefings in functional genomics
The way of co-administration of drugs is a sensible strategy for treating complex diseases efficiently. Because of existing massive unknown interactions among drugs, predicting potential adverse drug-drug interactions (DDIs) accurately is promotive t...

Deep learning tools are top performers in long non-coding RNA prediction.

Briefings in functional genomics
The increasing amount of transcriptomic data has brought to light vast numbers of potential novel RNA transcripts. Accurately distinguishing novel long non-coding RNAs (lncRNAs) from protein-coding messenger RNAs (mRNAs) has challenged bioinformatic ...

Pretraining model for biological sequence data.

Briefings in functional genomics
With the development of high-throughput sequencing technology, biological sequence data reflecting life information becomes increasingly accessible. Particularly on the background of the COVID-19 pandemic, biological sequence data play an important r...

Sequence representation approaches for sequence-based protein prediction tasks that use deep learning.

Briefings in functional genomics
Deep learning has been increasingly used in bioinformatics, especially in sequence-based protein prediction tasks, as large amounts of biological data are available and deep learning techniques have been developed rapidly in recent years. For sequenc...

Prediction of bio-sequence modifications and the associations with diseases.

Briefings in functional genomics
Modifications of protein, RNA and DNA play an important role in many biological processes and are related to some diseases. Therefore, accurate identification and comprehensive understanding of protein, RNA and DNA modification sites can promote rese...

Machine learning-based approaches for disease gene prediction.

Briefings in functional genomics
Disease gene prediction is an essential issue in biomedical research. In the early days, annotation-based approaches were proposed for this problem. With the development of high-throughput technologies, interaction data between genes/proteins have gr...

Machine learning and its applications in plant molecular studies.

Briefings in functional genomics
The advent of high-throughput genomic technologies has resulted in the accumulation of massive amounts of genomic information. However, biologists are challenged with how to effectively analyze these data. Machine learning can provide tools for bette...

Deep learning in omics: a survey and guideline.

Briefings in functional genomics
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fortunately,...

Application of supervised machine learning algorithms for the classification of regulatory RNA riboswitches.

Briefings in functional genomics
Riboswitches, the small structured RNA elements, were discovered about a decade ago. It has been the subject of intense interest to identify riboswitches, understand their mechanisms of action and use them in genetic engineering. The accumulation of ...