Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Gene Families01:57

Gene Families

9.3K
Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
9.3K
Protein Families02:47

Protein Families

16.1K
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...
16.1K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.5K
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...
6.5K
Classification of Systems-I01:26

Classification of Systems-I

362
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
362
Classification of Skeletal Muscle Fibers01:48

Classification of Skeletal Muscle Fibers

57.4K
Skeletal muscles continuously produce ATP to provide the energy that enables muscle contractions. Skeletal muscle fibers can be categorized into three types based on differences in their contraction speed and how they produce ATP, as well as physical differences related to these factors. Most human muscles contain all three muscle fiber types, albeit in varying proportions.
Slow-Twitch Muscle Fibers
Slow oxidative, muscle fibers appear red due to large numbers of capillaries and high levels of...
57.4K
Classification of Systems-II01:31

Classification of Systems-II

259
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
259

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

PMSA as a potential modulator of calcineurin phosphatase activity.

Scientific reports·2026
Same author

A rare JAK2 mutation associated with adult-onset Still's disease and exacerbated vaccine-induced innate immune response.

Rheumatology (Oxford, England)·2026
Same author

Antitumor immunotoxin expression is enhanced by Escherichia coli csrB-promoter activity.

Oncogene·2026
Same author

Role of Aspartate in Immune Response and Mortality in a Polymicrobial Sepsis Model: Insights from Metabolomics and Transcriptomics.

Cells·2026
Same author

Molecular phylogeny and morphometric divergence of native Korean wild mice (Mus musculus).

Laboratory animal research·2026
Same author

<i>STAT3<sup>R152W</sup></i> Mutation Model Reveals Temporal Changes in Hematopoietic Populations.

International journal of molecular sciences·2026

Related Experiment Video

Updated: Oct 16, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
08:04

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

646

PIC-Me: paralogs and isoforms classifier based on machine-learning approaches.

Jooseong Oh1, Sung-Gwon Lee1, Chungoo Park2

  • 1School of Biological Sciences and Technology, Chonnam National University, Gwangju, 61186, Republic of Korea.

BMC Bioinformatics
|October 22, 2021
PubMed
Summary

Accurately identifying gene paralogs and isoforms is crucial but challenging, especially in non-model organisms. This study introduces PIC-Me, a machine-learning tool that improves gene annotation accuracy using novel RNA-seq features.

Keywords:
Alternative splicingGene duplicationIsoformsMachine learningParalogsRNA-Seq

More Related Videos

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.6K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.2K

Related Experiment Videos

Last Updated: Oct 16, 2025

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
08:04

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

646
An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

3.6K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.2K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Gene duplication and alternative splicing generate protein diversity and maintain homeostasis.
  • Accurate annotation of gene loci for paralog and isoform identification is often incomplete.
  • Analyzing transcriptomes of non-model organisms without reference genomes presents significant challenges.

Purpose of the Study:

  • To develop a reliable method for discriminating between paralogs and isoforms in RNA-seq data.
  • To enhance gene annotation accuracy, particularly for non-model organisms.
  • To provide a valuable computational resource for the genomics community.

Main Methods:

  • Redefined existing sequence features (similarity, block counts, match-mismatch fraction).
  • Introduced new genomic and transcriptomic features (twilight zone, expression difference).
  • Validated features using Support Vector Machine (SVM) and Random Forest (RF) models on nine RNA-seq datasets.

Main Results:

  • Random Forest (RF) model achieved Area Under the Curve (AUC) scores over 0.9 across all datasets.
  • Proposed features significantly improved discrimination accuracy compared to existing methods.
  • The implemented PIC-Me tool, using an RF model, outperformed a previously existing method.

Conclusions:

  • PIC-Me, a machine-learning approach, effectively identifies paralogs and isoforms using RNA-seq data.
  • The tool demonstrates superior performance compared to existing methods.
  • PIC-Me is a valuable resource for gene annotation, comparative transcriptomics, and evolutionary genomics, especially for non-model organisms.