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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
RNA Interference01:23

RNA Interference

RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Nucleic Acid Structure01:25

Nucleic Acid Structure

The pentose sugar in DNA is deoxyribose, while in RNA the pentose sugar is ribose. The difference between the sugars is the presence of the hydroxyl group on the ribose's second carbon and a hydrogen on the deoxyribose's second carbon. The phosphate residue attaches to the hydroxyl group of the 5′ carbon of one sugar and the hydroxyl group of the 3′ carbon of the sugar of the next nucleotide, which forms  a 5′ to 3′ phosphodiester linkage.
DNA Structure
DNA has a double-helix structure. The...

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Updated: May 26, 2026

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions
10:52

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions

Published on: September 28, 2017

Predicting RNA-protein interactions using only sequence information.

Usha K Muppirala1, Vasant G Honavar, Drena Dobbs

  • 1Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa, USA. usha@iastate.edu

BMC Bioinformatics
|December 24, 2011
PubMed
Summary
This summary is machine-generated.

RPISeq accurately predicts RNA-protein interactions using only sequence data, offering a cost-effective computational method for constructing interaction networks. This tool aids in understanding RNA-protein interactions and non-coding RNA functions.

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Last Updated: May 26, 2026

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • RNA-protein interactions (RPIs) are crucial for cellular processes, including gene regulation and host defense.
  • Experimental identification of RPIs is costly and time-consuming, necessitating computational prediction methods.

Purpose of the Study:

  • To develop and evaluate RPISeq, a computational tool for predicting RNA-protein interactions solely from sequence information.
  • To establish a cost-effective and reliable method for building RNA-protein interaction networks.

Main Methods:

  • RPISeq utilizes sequence-derived features: RNA 4-mer composition and protein 3-mer composition based on a reduced alphabet.
  • Two classifiers were employed: Support Vector Machine (SVM) and Random Forest (RF).
  • Performance was assessed on benchmark datasets from the Protein-RNA Interface Database (PRIDB) and NPInter.

Main Results:

  • RPISeq achieved high predictive performance with AUC values of 0.96 and 0.92 on PRIDB datasets.
  • The method demonstrated competitive performance against existing tools requiring diverse feature sets for mRNA-protein interactions.
  • RPISeq successfully predicted a majority of non-coding RNA-protein interactions across multiple species.

Conclusions:

  • Sequence information alone is sufficient for reliable prediction of RNA-protein interactions.
  • RPISeq provides an economical approach for computational RNA-protein interaction network construction.
  • The tool offers valuable insights into the functional roles of non-coding RNAs.