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

The Stanford Prison Experiment03:20

The Stanford Prison Experiment

24.6K
The famous and controversial Stanford Prison Experiment, conducted by social psychologist Philip Zimbardo and his colleagues at Stanford University, demonstrated the power of social roles, social norms, and scripts.
24.6K
What is an Experiment?01:12

What is an Experiment?

17.6K
An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
17.6K
What is Natural Selection?01:32

What is Natural Selection?

126.6K
Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
126.6K
Antibiotic Selection00:57

Antibiotic Selection

59.6K
Overview
59.6K
Thomson's e/m Experiment01:19

Thomson's e/m Experiment

6.7K
In a beam of charged particles created by a heated cathode, the particles move at different speeds. However, many applications need a beam with uniform particle speeds. An arrangement known as a velocity selector uses electric and magnetic fields to pick particles with a particular speed from the beam.
A particle with charge q, speed v, and mass m enters an area from the top, where the magnetic and electric fields are perpendicular both to the particle's motion and to one another. The magnetic...
6.7K
Types of Selection01:46

Types of Selection

44.3K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
44.3K

You might also read

Related Articles

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

Sort by
Same author

Accurately programming complex light regimes with multichannel LEDs.

Quantitative plant biology·2026
Same author

Stable and dynamic gene expression patterns over diurnal and developmental timescales in Arabidopsis thaliana.

The New phytologist·2025
Same author

Single-plant-omics reveals the cascade of transcriptional changes during the vegetative-to-reproductive transition.

The Plant cell·2024
Same author

Variation of terpene alkaloids in Daphniphyllum macropodum across plants and tissues.

The New phytologist·2024
Same author

AraLeTA: An Arabidopsis leaf expression atlas across diurnal and developmental scales.

Plant physiology·2024
Same author

Complex epistatic interactions between ELF3, PRR9, and PRR7 regulate the circadian clock and plant physiology.

Genetics·2023
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Jan 26, 2026

Longitudinal Follow-Up of Urinary Tract Infections and Their Treatment in Mice using Bioluminescence Imaging
07:39

Longitudinal Follow-Up of Urinary Tract Infections and Their Treatment in Mice using Bioluminescence Imaging

Published on: June 14, 2021

3.5K

NITPicker: selecting time points for follow-up experiments.

Daphne Ezer1,2, Joseph Keir3

  • 1Department of Statistics, University of Warwick, Coventry, CV4 7AL, UK. dezer@turing.ac.uk.

BMC Bioinformatics
|April 4, 2019
PubMed
Summary
This summary is machine-generated.

NITPicker is a new tool that helps researchers choose optimal time points for experiments. It reduces bias and maximizes information, leading to stronger scientific conclusions.

Keywords:
DynamicsExperimental designFunctional data analysisLongitudinalRNA-seqTime series

More Related Videos

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
08:33

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

7.5K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.9K

Related Experiment Videos

Last Updated: Jan 26, 2026

Longitudinal Follow-Up of Urinary Tract Infections and Their Treatment in Mice using Bioluminescence Imaging
07:39

Longitudinal Follow-Up of Urinary Tract Infections and Their Treatment in Mice using Bioluminescence Imaging

Published on: June 14, 2021

3.5K
A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences
08:33

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

7.5K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.9K

Area of Science:

  • Statistics
  • Experimental Design
  • Functional Data Analysis

Background:

  • Experimental design critically influences measurement capabilities and result confidence.
  • Optimal design choices are vital to avoid systematic bias and strengthen statistical conclusions.
  • Selecting appropriate sampling times is crucial in time-series experiments to capture dynamic changes.

Purpose of the Study:

  • To develop a tool, NITPicker (Next Iteration Time-point Picker), for optimal time-point selection in experiments.
  • To eliminate decision-making biases in time-point selection.
  • To maximize the information gained about underlying data patterns.

Main Methods:

  • Utilizes principles from functional data analysis.
  • Develops an automated tool for selecting optimal sampling points.
  • Provides open-source code for implementation and visualization.

Main Results:

  • NITPicker effectively selects optimal time points, reducing human bias.
  • The tool maximizes the information captured about the shape of underlying curves.
  • Demonstrates robust performance across various real-world datasets.

Conclusions:

  • NITPicker is a valuable tool for optimizing experimental design.
  • Applicable to diverse biological fields, including longitudinal gene expression, weather patterns, and growth curves.
  • Enhances the reliability and interpretability of experimental findings.