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

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.9K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.9K
Genomics02:02

Genomics

38.0K
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...
38.0K
Microorganisms in Medicine and Therapeutics01:29

Microorganisms in Medicine and Therapeutics

487
Microorganisms play a fundamental role in vaccine development, gene therapy, and therapeutic production. Their biological properties are harnessed to advance medicine and public health. Beyond immunization, microorganisms contribute to gut health, antibiotic synthesis, and genetic disease treatment.Live Attenuated and Inactivated VaccinesLive attenuated vaccines, such as the measles, mumps, and rubella (MMR) vaccine, utilize weakened forms of pathogens to closely resemble natural infections.
487
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

5.2K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
5.2K
Human Genetics01:28

Human Genetics

810
Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
810

You might also read

Related Articles

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

Sort by
Same author

Seasonal Variation and Genetic Evaluation of Needle Catechin Content in Half-Sib Families of <i>Pinus taeda</i>.

Plants (Basel, Switzerland)·2026
Same author

Realistic PET image synthesis from MRI for automated inference of brain atrophy and Alzheimer's.

iScience·2026
Same author

Deep Continuous-Time State-Space Models for Marked Event Sequences.

Advances in neural information processing systems·2026
Same author

Reply.

Gastroenterology·2026
Same author

<i>Trans</i>-eQTLs reveal the architecture of human gene regulatory networks.

medRxiv : the preprint server for health sciences·2026
Same author

Transcriptome-Based Dissection of the Molecular Mechanisms Underlying Flooding Stress Responses of Eastern Cottonwood in the Floodplains of the Middle and Lower Reaches of the Yangtze River.

Plants (Basel, Switzerland)·2026
Same journal

Zero-shot reconstruction of mutant spatial transcriptomes.

Patterns (New York, N.Y.)·2026
Same journal

Dendritic nonlinearities mitigate communication costs.

Patterns (New York, N.Y.)·2026
Same journal

Erratum: Agentic AI as a coordination paradigm in digital health and agri-food systems.

Patterns (New York, N.Y.)·2026
Same journal

Spacing effect improves generalization in biological and artificial systems.

Patterns (New York, N.Y.)·2026
Same journal

A multi-modal foundation model for brain disease diagnosis and medical imaging.

Patterns (New York, N.Y.)·2026
Same journal

DuoMod-Net: Logarithmic balancing and geometric refinement for imbalanced semi-supervised medical image segmentation.

Patterns (New York, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Oct 15, 2025

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

1.1K

Machine learning applications for therapeutic tasks with genomics data.

Kexin Huang1, Cao Xiao2, Lucas M Glass3

  • 1Department of Computer Science, Stanford University, Stanford, CA 94305, USA.

Patterns (New York, N.Y.)
|October 25, 2021
PubMed
Summary
This summary is machine-generated.

Machine learning in genomics accelerates therapeutic development by analyzing diverse biomedical data. This review covers 22 applications across the drug pipeline, highlighting key challenges and future opportunities.

Keywords:
genomicsmachine learningtherapeutics discovery and development

More Related Videos

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

151
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.4K

Related Experiment Videos

Last Updated: Oct 15, 2025

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

1.1K
Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
03:08

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

151
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.4K

Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Genomics

Background:

  • Increasing availability of genomics and biomedical data fuels machine learning (ML) applications in drug discovery.
  • ML algorithms offer powerful tools for analyzing complex biological datasets.
  • Therapeutic development relies on integrating diverse data types for effective drug design and clinical application.

Purpose of the Study:

  • To survey machine learning applications in genomics within the context of therapeutic development.
  • To explore the integration of genomics with other data modalities like electronic health records and clinical texts.
  • To identify current challenges and future research directions in ML for genomics-driven therapeutics.

Main Methods:

  • Systematic literature review of machine learning applications in genomics for drug discovery and development.
  • Analysis of the interplay between genomics, compounds, proteins, electronic health records, cellular images, and clinical texts.
  • Categorization of ML applications across the entire therapeutics pipeline.

Main Results:

  • Identified 22 distinct machine learning in genomics applications spanning the full therapeutics pipeline.
  • Investigated the integration of genomics with diverse data sources including EHRs, imaging, and text data.
  • Highlighted key challenges and areas for future expansion in the field.

Conclusions:

  • Machine learning significantly enhances various stages of therapeutic development, from target identification to post-market analysis.
  • The integration of multi-modal data with genomics presents a promising avenue for advancing precision medicine.
  • Addressing identified challenges is crucial for unlocking the full potential of ML in genomics for future therapeutics.