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

Genetic Screens02:46

Genetic Screens

5.0K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
5.0K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.0K
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...
6.0K
Sampling Methods: Overview01:06

Sampling Methods: Overview

396
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
396
Sampling Plans01:23

Sampling Plans

230
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
230
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

319
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
319
Systematic Sampling Method01:17

Systematic Sampling Method

10.5K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
10.5K

You might also read

Related Articles

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

Sort by
Same author

Antioxidants Differentially Regulate Non-Photochemical Quenching.

Plant, cell & environment·2026
Same author

KBase: Open-source Platform for Collaborative Biological Data Analysis and Publication.

Journal of molecular biology·2026
Same author

Overexpression of 2-mercaptoethanesulfonate biosynthesis genes <i>comDE</i> protects methane-producing archaea from oxidative stress.

Journal of bacteriology·2025
Same author

Mer overexpression in <i>Methanosarcina acetivorans</i> affects growth and methanogenesis during substrate adaptation.

Applied and environmental microbiology·2025
Same author

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species.

GigaScience·2025
Same author

Coenzyme M: An Archaeal Antioxidant as an Agricultural Biostimulant.

Antioxidants (Basel, Switzerland)·2025
See all related articles

Related Experiment Video

Updated: Aug 8, 2025

Development and Testing of Species-specific Quantitative PCR Assays for Environmental DNA Applications
08:54

Development and Testing of Species-specific Quantitative PCR Assays for Environmental DNA Applications

Published on: November 5, 2020

13.6K

BioSIMP: Using Software Testing Techniques for Sampling and Inference in Biological Organisms.

Mikaela Cashman1, Jennie L Catlett2, Myra B Cohen1

  • 1Dept. of Computer Science & Engineering, University of Nebraksa-Lincoln, Lincoln, NE, USA.

Se4Science 2017 : 2017 IEEE/ACM 12Th International Workshop on Software Engineering for Science : Proceedings : 22 May 2017, Buenos Aires, Argentina. International Workshop on Software Engineering for Science (2017 : Buenos Aires, Argen
|February 27, 2023
PubMed
Summary
This summary is machine-generated.

Software engineering techniques can model biological systems. BioSIMP predicts microbial behavior and identifies key environmental factors, highlighting the need for advanced computational methods in systems biology.

Keywords:
Highly-Configurable SoftwareSystems Biology

More Related Videos

An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

7.3K
The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan
11:58

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

Published on: June 29, 2018

9.5K

Related Experiment Videos

Last Updated: Aug 8, 2025

Development and Testing of Species-specific Quantitative PCR Assays for Environmental DNA Applications
08:54

Development and Testing of Species-specific Quantitative PCR Assays for Environmental DNA Applications

Published on: November 5, 2020

13.6K
An Unbiased Approach of Sampling TEM Sections in Neuroscience
10:56

An Unbiased Approach of Sampling TEM Sections in Neuroscience

Published on: April 13, 2019

7.3K
The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan
11:58

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

Published on: June 29, 2018

9.5K

Area of Science:

  • Computational Biology
  • Systems Biology
  • Software Engineering

Background:

  • Software engineering offers advanced methods for analyzing complex systems.
  • Nature-inspired algorithms (genetic algorithms, swarm intelligence) have influenced software engineering.
  • Systems biology requires robust tools for modeling and prediction.

Purpose of the Study:

  • To introduce BioSIMP, a novel process for modeling and predicting biological organism behavior.
  • To apply software engineering principles to the field of systems biology.
  • To identify critical environmental factors influencing microbial organisms.

Main Methods:

  • Utilizing techniques from testing and modeling of highly-configurable software systems.
  • Applying the BioSIMP process to analyze biological data.
  • Integrating experimental and simulation data for validation.

Main Results:

  • BioSIMP successfully modeled and predicted the behavior of two microbial organisms.
  • The process identified significant environmental factors impacting microbial life.
  • Demonstrated the utility of software engineering approaches in biological research.

Conclusions:

  • BioSIMP is a promising tool for systems biology, leveraging software engineering expertise.
  • Further development of software engineering techniques is necessary to address biological complexity.
  • Interdisciplinary approaches are crucial for advancing systems biology research.