AI Medical Compendium Topic

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Databases, Nucleic Acid

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High-throughput developability assays enable library-scale identification of producible protein scaffold variants.

Proceedings of the National Academy of Sciences of the United States of America
Proteins require high developability-quantified by expression, solubility, and stability-for robust utility as therapeutics, diagnostics, and in other biotechnological applications. Measuring traditional developability metrics is low throughput in na...

scCancer: a package for automated processing of single-cell RNA-seq data in cancer.

Briefings in bioinformatics
Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis and treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer cell heterogeneities and microenv...

DeepATT: a hybrid category attention neural network for identifying functional effects of DNA sequences.

Briefings in bioinformatics
Quantifying DNA properties is a challenging task in the broad field of human genomics. Since the vast majority of non-coding DNA is still poorly understood in terms of function, this task is particularly important to have enormous benefit for biology...

Integrative biomarker detection on high-dimensional gene expression data sets: a survey on prior knowledge approaches.

Briefings in bioinformatics
Gene expression data provide the expression levels of tens of thousands of genes from several hundred samples. These data are analyzed to detect biomarkers that can be of prognostic or diagnostic use. Traditionally, biomarker detection for gene expre...

SilencerDB: a comprehensive database of silencers.

Nucleic acids research
Gene regulatory elements, including promoters, enhancers, silencers, etc., control transcriptional programs in a spatiotemporal manner. Though these elements are known to be able to induce either positive or negative transcriptional control, the comm...

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.

Protein and peptide letters
In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well ...

High-throughput phenotyping with deep learning gives insight into the genetic architecture of flowering time in wheat.

GigaScience
BACKGROUND: Measurement of plant traits with precision and speed on large populations has emerged as a critical bottleneck in connecting genotype to phenotype in genetics and breeding. This bottleneck limits advancements in understanding plant genome...

BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches.

Briefings in bioinformatics
With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typi...

Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNA that regulate gene expression through post-transcriptional silencing. Differential expression observed in miRNAs, combined with advancements in deep learning (DL), have the potential to improve...