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

Fischer Projections02:18

Fischer Projections

16.4K
Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
16.4K
Newman Projections02:06

Newman Projections

20.7K
Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
The organic molecules rotate across the single bonds leading to numerous temporary three-dimensional structures of varying energy known as...
20.7K
Coordinates and Map Projections01:29

Coordinates and Map Projections

602
Coordinates and map projections are essential tools in accurately representing the Earth's surface for various applications, ranging from navigation to spatial analysis. The latitude and longitude coordinate system is a universally recognized framework for defining locations. Latitude specifies the distance of a point north or south of the equator, measured in degrees from 0° at the equator to 90° at the poles. Longitude indicates a location's position east or west of the prime meridian,...
602
Dietary Connections01:23

Dietary Connections

61.6K
In biological systems, most metabolic pathways are interconnected. The cellular respiration processes that convert glucose to ATP—such as glycolysis, pyruvate oxidation, and the citric acid cycle—tie into those that break down other organic compounds. As a result, various foods—from apples to cheese to guacamole—end up as ATP. In addition to carbohydrates, food also contains proteins and lipids—such as cholesterol and fats. All of these organic compounds are used...
61.6K
Functions of Connective Tissues01:17

Functions of Connective Tissues

15.0K
Connective tissues perform a broad range of functions in the body. Their primary function is to connect and link different tissues in the body and act as packaging material between tissues. The areolar tissue, a connective tissue prototype, commonly cements various tissue types in diverse body organs. In contrast, adipose tissue cushions internal organs while insulating the body from heat loss.
Hard connective tissues, such as bones and cartilage, provide structure and support to the body.
15.0K
Loose Connective Tissue01:26

Loose Connective Tissue

9.4K
Loose connective tissue is found between many organs. Its main function is to absorb shock and bind tissues together. It also allows water, salts, and various nutrients to diffuse into cells that are embedded in it or present in adjacent tissues.
Adipose Tissue
Adipose tissue consists primarily of fat storage cells called adipocytes and little extracellular matrix. A large number of capillaries present within adipose tissue allow rapid mobilization of lipid molecules. White adipose tissue is...
9.4K

You might also read

Related Articles

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

Sort by
Same author

An in vivo platform to jointly monitor cellular and metabolic responses to chemotherapy.

bioRxiv : the preprint server for biology·2026
Same author

Single-cell RNA profiling of oligodendroglial lineage cells derived from iPSCs carrying Parkinson's disease-relevant LRRK2-G2019S mutation.

iScience·2026
Same author

Scoring gene importance by interpreting single-cell foundation models.

Nature biotechnology·2026
Same author

Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues.

Genome biology·2026
Same author

Wild-type <i>C9orf72</i> expression is a genetic modifier of C9-ALS survival.

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

Integration of multiomic and multi-phenotypic data identifies biological pathways associated with physical fitness.

Communications biology·2026
Same journal

Trust, Reproducibility, and Progress: The Roles of Independent Blind Prediction and Assessment and Benchmarking in Computational Biology.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Applications of AI & ML in Biomanufacturing of Cell and Gene Therapies.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

AI for Health: Leveraging Artificial Intelligence to Revolutionize Healthcare.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

Workshop Introduction: Advances of AI Methods in Single Cell Spatial Omics.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
Same journal

DRIVE-KG: Enhancing variant-phenotype association discovery in understudied complex diseases using heterogeneous knowledge graphs.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing·2026
See all related articles

Related Experiment Video

Updated: Jan 26, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.3K

Shallow Sparsely-Connected Autoencoders for Gene Set Projection.

Maxwell P Gold1, Alexander LeNail1, Ernest Fraenkel1

  • 1Department of Biological Engineering, Massachusetts Institute of Technology, 21 Ames St. Cambridge, MA, 02139, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|April 10, 2019
PubMed
Summary
This summary is machine-generated.

New machine learning methods, shallow sparsely-connected autoencoders (SSCAs) and variational autoencoders (SSCVA), project gene data onto gene sets. SSCVA demonstrates superior performance in classification and prediction tasks compared to SSCA and existing algorithms.

Keywords:
autoencodergene setsingle-cell RNA-Sequencingvariational autoencoder

More Related Videos

Shallow Water Paddling Variants of Water Maze Tests in Mice
07:47

Shallow Water Paddling Variants of Water Maze Tests in Mice

Published on: June 3, 2013

24.3K
The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project
06:52

The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project

Published on: November 12, 2009

15.6K

Related Experiment Videos

Last Updated: Jan 26, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.3K
Shallow Water Paddling Variants of Water Maze Tests in Mice
07:47

Shallow Water Paddling Variants of Water Maze Tests in Mice

Published on: June 3, 2013

24.3K
The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project
06:52

The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project

Published on: November 12, 2009

15.6K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Machine Learning in Genomics

Background:

  • Gene set analysis is crucial for interpreting biological data.
  • Existing methods for differential gene set identification are limited.
  • Advancements in large-scale datasets like single-cell RNA-Sequencing necessitate sophisticated analytical tools.

Purpose of the Study:

  • To introduce shallow sparsely-connected autoencoders (SSCAs) and variational autoencoders (SSCVA) for gene set analysis.
  • To evaluate the efficacy of SSCAs and SSCVA in projecting gene-level data onto biologically relevant gene sets.
  • To compare the performance of SSCVA against SSCA and established gene set scoring algorithms.

Main Methods:

  • Development and application of shallow sparsely-connected autoencoders (SSCAs).
  • Development and application of shallow sparsely-connected variational autoencoders (SSCVA).
  • Testing on single-cell RNA-Sequencing data from blood cells and RNA-Sequencing data from breast cancer patients.

Main Results:

  • Both SSCA and SSCVA successfully recover known biological features from diverse datasets.
  • SSCVA demonstrates enhanced performance over SSCA in classification and prediction tasks.
  • SSCVA outperforms six existing gene set scoring algorithms in tested benchmarks.

Conclusions:

  • SSCAs and SSCVA are effective tools for gene set analysis using modern biological datasets.
  • SSCVA offers an improved approach for gene set analysis, particularly for classification and prediction.
  • These methods advance the application of machine learning in interpreting complex genomic data.