Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Synthetic Biology

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

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...

You might also read

Related Articles

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

Sort by

Same author

[Driving mechanism of dissolved inorganic carbon on the carbon sink/source changes in Tianchi Lake, Huaying Mountain, Sichuan, China].

Ying yong sheng tai xue bao = The journal of applied ecology·2026

Same author

[Anti-arthritis effects of total triterpenoids from fruits of Chaenomeles speciosa based on TLR4/NF-κB/NLRP3 signaling pathway].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2026

Same author

Spinulactones A-F: Bioactive Drimane-Type Sesquiterpenes from the Endophytic <i>Penicillium spinulosum</i> 9-1.

Journal of natural products·2025

Same author

The Economic Burden of Brucellosis Care in China: Socioeconomic Status Inequality.

Journal of tropical medicine·2024

Same author

Tormentic acid, a triterpenoid isolated from the fruits of <i>Chaenomeles speciose</i>, protected indomethacin-induced gastric mucosal lesion via modulating miR-139 and the CXCR4/CXCL12/PLC/PKC/Rho a/MLC pathway.

Pharmaceutical biology·2023

Same author

Enhanced dehalogenation of brominated DBPs by catalyzed electrolysis using Vitamin B<sub>12</sub> modified electrodes: Kinetics, mechanisms, and mass balances.

Journal of hazardous materials·2023

Search research articles

Related Experiment Video

Updated: Jun 8, 2026

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

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

Published on: July 22, 2025

Compact extreme learning machines for biological systems.

Kang Li¹, Jing Deng, Hai-Bo He

¹School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, UK. k.li@qub.ac.uk

International Journal of Computational Biology and Drug Design

|September 21, 2010

Summary

This summary is machine-generated.

This study introduces a sparse Extreme Learning Machine (ELM) for biological system modeling. The improved method enhances model compactness and sparsity without adding computational complexity.

More Related Videos

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Published on: October 10, 2025

Related Experiment Videos

Last Updated: Jun 8, 2026

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

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

Published on: July 22, 2025

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on: December 15, 2023

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Published on: October 10, 2025

Area of Science:

Computational Biology
Machine Learning

Background:

Data-driven black-box methods are crucial for biological system modeling.
Extreme Learning Machines (ELMs) offer fast learning but lack inherent model sparsity.
Parsimonious models are essential for efficient system representation.

Purpose of the Study:

To develop an improved Extreme Learning Machine (ELM) for enhanced model sparsity.
To achieve a more compact model without increasing computational complexity.
To enhance the efficiency of biological system modeling.

Main Methods:

An improved Extreme Learning Machine (ELM) approach was investigated.
Regularization parameters were associated with model terms.
Insignificant terms were automatically unselected to promote sparsity.

Main Results:

The improved ELM demonstrated enhanced model sparsity.
Model compactness was achieved without significant computational overhead.
Effectiveness was confirmed through experimental results on biochemical data.

Conclusions:

The proposed method effectively generates sparse and parsimonious models.
This approach improves the efficiency of data-driven biological system modeling.
The technique offers a valuable tool for computational biology applications.