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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.8K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
15.8K
Biological Causes of Schizophrenia01:29

Biological Causes of Schizophrenia

681
Schizophrenia, a severe psychiatric disorder, arises from a complex interplay of biological factors, including genetic predisposition, structural brain abnormalities, neurotransmitter dysregulation, and developmental irregularities. These factors collectively contribute to the onset and progression of the disorder, which typically manifests in late adolescence or early adulthood.
Genetic Factors in Schizophrenia
The genetic basis of schizophrenia is strongly supported by family and twin...
681
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

18.6K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
18.6K
Psychological and Sociocultural Causes of Schizophrenia01:29

Psychological and Sociocultural Causes of Schizophrenia

656
Schizophrenia, a complex psychiatric disorder, has been historically misunderstood. Early psychological theories attributed its origins to childhood trauma and unresponsive parenting. However, contemporary research largely rejects these notions, favoring the vulnerability-stress hypothesis. This model proposes that individuals with a genetic predisposition to schizophrenia may develop the disorder following exposure to significant environmental stressors. Notably, studies on high-risk...
656
Psychosis: Pathophysiology of Schizophrenia and Other Psychotic Disorders01:27

Psychosis: Pathophysiology of Schizophrenia and Other Psychotic Disorders

2.1K
Schizophrenia is a neurodevelopmental disorder whose origins are rooted in complex genetic components. Despite our burgeoning understanding, the pathophysiology of this disorder remains incompletely deciphered.
Researchers have identified genetic factors that increase susceptibility to schizophrenia, underscoring the intricate interplay between genetics and environment in disease development. At the core of schizophrenia's pathophysiology is excessive dopaminergic neurotransmission within...
2.1K

You might also read

Related Articles

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

Sort by
Same author

Understanding the role of hypertension in stroke outcomes using Bayesian analysis.

Scientific reports·2025
Same author

An intelligent YOLO and CNN-BiGRU framework for road infrastructure based anomaly assessment.

Scientific reports·2025
Same author

Study of the Patterns of DNA Methylation in Human Cells Through the Prism of Intra-Strand DNA Symmetry.

International journal of molecular sciences·2025
Same author

Behind the care: emotional struggles, burnout, and denial in kazakhstan's professional palliative care workforce.

BMC palliative care·2025
Same author

The Regional Burden of Parkinson's Disease in Kazakhstan 2014-2021: Insights From National Health Data.

Parkinson's disease·2025
Same author

Predicting Intensive Care Unit Admission in COVID-19-Infected Pregnant Women Using Machine Learning.

Journal of clinical medicine·2025
Same journal

MOREshiny: a user-friendly application for the inference of phenotype-specific multi-omic regulatory networks.

Bioinformatics advances·2026
Same journal

spammR: an R package designed for analysis and integration of spatial multi-omic measurements.

Bioinformatics advances·2026
Same journal

Interpretable prediction and generation of ASC-speck aptamers using multiscale deep biological learning models.

Bioinformatics advances·2026
Same journal

vClassifier: a toolkit for high-resolution phylogenetic classification of prokaryotic viruses.

Bioinformatics advances·2026
Same journal

GWAIS-Web: a free and secure web service for ultra-fast and large-scale genome-wide association interaction studies.

Bioinformatics advances·2026
Same journal

Folding the unfoldable 2: using AlphaFold and ESMFold to explore spurious proteins.

Bioinformatics advances·2026
See all related articles

Related Experiment Video

Updated: Feb 17, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K

SNP-based prediction of schizophrenia using machine learning.

Zamart Ramazanova1,2, Bakhyt Matkarimov2,3, Sheida Nabavi4

  • 1Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, 53 Kabanbay Batyr Avenue, Astana, 010000, Kazakhstan.

Bioinformatics Advances
|February 16, 2026
PubMed
Summary
This summary is machine-generated.

This study predicts schizophrenia risk using genetic data (SNPs). Machine learning models showed high accuracy, especially for African-American females and European-American males, suggesting potential clinical utility.

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.3K
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

1.6K

Related Experiment Videos

Last Updated: Feb 17, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.3K
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

1.6K

Area of Science:

  • Psychiatric Genetics
  • Computational Biology
  • Population Genetics

Background:

  • Schizophrenia affects ~0.32% globally, characterized by cognitive and emotional deficits.
  • Understanding the genetic architecture of schizophrenia is vital for identifying pathogenic variants.
  • Single nucleotide polymorphisms (SNPs) are key genetic markers for complex disorders.

Purpose of the Study:

  • To assess the feasibility of predicting schizophrenia using an individual's SNP profile.
  • To develop ethnicity- and gender-specific predictive models for schizophrenia.
  • To identify significantly associated SNPs for schizophrenia risk.

Main Methods:

  • Utilized genome-wide association (GWA) data from 4693 participants (European-American and African-American).
  • Employed machine learning techniques for SNP-based predictive model construction.
  • Applied feature selection, association analysis, and stratified five-fold cross-validation.

Main Results:

  • Developed ethnicity-gender-specific models (EA-F, EA-M, AA-F, AA-M) with varying accuracies.
  • Achieved classification accuracies (AUC) of 75.1% (EA-F), 65.4% (EA-M), 68.6% (AA-F), and 73.9% (AA-M).
  • Models for AA-F, EA-F, and EA-M demonstrated high sensitivity (>70%), indicating potential as auxiliary clinical tools.

Conclusions:

  • SNP-based prediction models show feasibility in assessing schizophrenia risk.
  • Ethnicity- and gender-specific models offer tailored risk assessment potential.
  • High-sensitivity models can aid in early risk identification for specific populations.