AIMC Topic: Multiomics

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CustOmics: A versatile deep-learning based strategy for multi-omics integration.

PLoS computational biology
The availability of patient cohorts with several types of omics data opens new perspectives for exploring the disease's underlying biological processes and developing predictive models. It also comes with new challenges in computational biology in te...

Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer.

Seminars in cancer biology
Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed of tumor and stromal cellular components; at the genetic levels, they comprise genetically distinct ...

A fair experimental comparison of neural network architectures for latent representations of multi-omics for drug response prediction.

BMC bioinformatics
BACKGROUND: Recent years have seen a surge of novel neural network architectures for the integration of multi-omics data for prediction. Most of the architectures include either encoders alone or encoders and decoders, i.e., autoencoders of various s...

DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics.

Scientific reports
Modern oncology offers a wide range of treatments and therefore choosing the best option for particular patient is very important for optimal outcome. Multi-omics profiling in combination with AI-based predictive models have great potential for strea...

Multi-omics integration method based on attention deep learning network for biomedical data classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Integrating multi-omics data for the comprehensive analysis of the biological processes in human diseases has become one of the most challenging tasks of bioinformatics. Deep learning (DL) algorithms have recently become one...

Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence.

Journal of the American Chemical Society
Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) ...

The need for an integrated multi-OMICs approach in microbiome science in the food system.

Comprehensive reviews in food science and food safety
Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing dema...

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine.

Seminars in cancer biology
With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics tec...

Clustering of single-cell multi-omics data with a multimodal deep learning method.

Nature communications
Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. It provides a unique opportunity to jointly analyze multimodal data at the single-cell level for the identification ...