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Related Concept Videos

RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
FISH - Fluorescent In-situ Hybridization02:07

FISH - Fluorescent In-situ Hybridization

Fluorescence in situ hybridization, or FISH, was developed in the early 1980s and has quickly become one of the most widely used techniques in cytogenetics. Labeled probes are used to bind complementary DNA or RNA sequences on a chromosome or in a region within a cell. Earlier, the probes could only be obtained by cloning or reverse transcription of a DNA template. Currently, the probe oligonucleotides can be synthesized synthetically. Additionally, with the advancement of optical techniques,...
Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
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Related Experiment Videos

ARISE: RNA-anchored shared-edge topology and hierarchical fusion for spatial multi-omics integration.

Xiangxiang Wang1, Yanchi Su2, Gaoyang Hao1

  • 1School of Artificial Intelligence, Jilin University, Changchun 130012, China.

Bioinformatics (Oxford, England)
|June 29, 2026
PubMed
Summary

ARISE integrates spatial multi-omics data by anchoring on RNA expression, improving spatial domain identification and cross-modal consistency. This novel framework enhances tissue structure preservation and downstream biological analysis for robust spatial multi-omics integration.

Related Experiment Videos

Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics

Background:

  • Spatial multi-omics technologies offer in situ profiling of transcriptomes, proteins, and chromatin accessibility for tissue organization analysis.
  • Existing graph-based integration methods struggle with sparse or noisy auxiliary modalities, leading to discordant graphs and reduced spatial resolution.
  • Topological discordance in modality-specific graphs can weaken cross-modal alignment and propagate spurious edges.

Purpose of the Study:

  • To develop a novel framework for robust spatial multi-omics integration that overcomes limitations of existing methods.
  • To improve spatial domain identification, cross-modal consistency, and tissue structure preservation in spatial multi-omics data.
  • To provide a principled and interpretable method for analyzing complex spatial multi-omics datasets.

Main Methods:

  • ARISE (Anchored RNA for Integrated Spatial Embedding) framework utilizes RNA expression as an anchor for integration.
  • A shared-edge topology is defined by intersecting RNA feature-similarity and spatial-proximity graphs.
  • Auxiliary modalities are encoded on the common scaffold and integrated via inside-out hierarchical fusion.

Main Results:

  • ARISE improves spatial domain identification and cross-modal consistency across simulated and real bi-modal and tri-modal datasets.
  • The framework demonstrates enhanced preservation of tissue structure compared to existing methods.
  • Learned representations support biologically meaningful downstream analyses, including marker-based annotation and pathway enrichment.

Conclusions:

  • ARISE provides a robust and interpretable framework for spatial multi-omics integration.
  • The method effectively addresses challenges posed by sparse or noisy auxiliary modalities.
  • ARISE enhances the biological insights derived from spatial multi-omics data.