Bioinformatics Machine learning methods for omics data integration IOWA STATE UNIVERSITY Julie A. Dickerson ZhouWengangHigh-throughput technologies produce genome-scale transcriptomic and metabolomic (omics) da
Many computational scientists have tackled the integration problem and at least 250 tools for single-cell integration are now available2. Studies have evaluated the performance of some methods3,4,5,6, leading to a set of established metrics for assessing integration performance. While the methods ...
Deep learning-based models for preimplantation mouse and human embryos based on single-cell RNA sequencing This Resource uses deep learning-based tools to build a dynamic transcriptomic reference for mouse and human preimplantation development. Martin Proks , Nazmus Salehin & Joshua M. Brickman Res...
The use of multi-omics data in clinical settings is promising as it can provide information for accurate diagnosis and targeted therapy. However, challenges pertain to the development of software tools with robust and transparent mathematical methods, active engagement and training of clinicians in new...
), we systematically classified existing methods and tools for various types of integrative proteogenomic studies into four major sections. Sequence-centric Proteogenomics describes aspects of sequence-centric proteogenomics and the combined use of genomic and proteomic data to augment gene or protein ...
为应对这一挑战,一种名为SpatialData的开放式和通用数据框架应运而生(3月20日Nature Methods“SpatialData: an open and universal data framework for spatial omics”)。这一框架旨在为空间组学数据提供一个统一和可扩展的多平台文件格式,同时...
Multi-omics research is increasingly recognized as being important for understanding and prediction of complex diseases. Driven by technological advances, ...
In total we identified 305 tools and databases (Fig.1). We classified them in three broad categories:data,tools for single traitsandtools for multiple traits, along with the various sub-categories. The total breakdown is given in Table1. Several tools may perform different tasks and thus they...
A few reviews exist on this topic. For example, Berger et al. [1] described integrative approaches in one of the sections of their work, which is also focused on tools for the analysis of single omics layers, while Kristensen et al. [2] presented objectives, methods and computational tools...
SpatialGlue is a tool designed to decipher spatial domains from spatial multi-omics data acquired from a single tissue section. It employes graph neural networks with a dual-attention mechanism to accomplish within-omics integration of measured features and spatial information, followed by cross-omics...