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Protein Networks02:26

Protein Networks

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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.
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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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. 
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Protein Families02:47

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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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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.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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A Protocol for Computer-Based Protein Structure and Function Prediction
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PASS: Protein Annotation Surveillance Site for Protein Annotation Using Homologous Clusters, NLP, and Sequence

Jin Tao1, Kelly A Brayton1,2,3, Shira L Broschat1,2,3

  • 1School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, United States.

Frontiers in Bioinformatics
|October 28, 2022
PubMed
Summary
This summary is machine-generated.

The Protein Annotation Surveillance Site (PASS) website aids life scientists in accurate protein annotation. It uses a large sequence database and machine learning to verify protein functions, improving genome annotation quality.

Keywords:
homologous clustersmachine learningnatural language processingnetwork scienceprotein annotationweb application

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome sequencing advances have outpaced annotation quality.
  • Computational protein annotation lacks sufficient experimental verification, leading to errors.
  • Accurate protein annotation tools are crucial for life scientists.

Purpose of the Study:

  • To introduce the Protein Annotation Surveillance Site (PASS) website.
  • To provide a tool for accurate protein annotation.
  • To address challenges in genome and protein annotation quality.

Main Methods:

  • Developed a website (PASS) with three components.
  • Integrated a database of over 8 million homologous protein sequences from diverse genomes.
  • Implemented machine learning to query UniProtKB for experimental verification of protein function.
  • Created a queryable webpage returning FASTA headers for similarity network construction.

Main Results:

  • PASS provides a database of homologous protein clusters.
  • PASS utilizes machine learning to identify experimentally verified protein functions.
  • Users can generate sequence similarity networks for annotation assistance.

Conclusions:

  • PASS offers a valuable tool for improving protein annotation accuracy.
  • The website aids life scientists in navigating annotation challenges.
  • PASS contributes to reducing annotation error propagation in genomic data.