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

Mean free path and Mean free time01:22

Mean free path and Mean free time

5.1K
Consider the gas molecules in a cylinder. They move in a random motion as they collide with each other and change speed and direction. The average of all the path lengths between collisions is known as the "mean free path."
5.1K
Path Between Thermodynamics States01:21

Path Between Thermodynamics States

4.0K
Consider the two thermodynamic processes involving an ideal gas that are represented by paths AC and ABC in Figure 1:
4.0K
Interference: Path Lengths01:10

Interference: Path Lengths

2.2K
Consider two sources of sound, that may or may not be in phase, emitting waves at a single frequency, and consider the frequencies to be the same.
Two special sources may be considered when they are in phase. This can be easily achieved by feeding the two sources from the same source. An example would be synchronizing the two speakers by feeding them with the same source, such as the sound waves produced by a tuning fork. This setup ensures that the two sources have the same frequency and are...
2.2K
Nuclear Stability03:18

Nuclear Stability

23.3K
Protons and neutrons, collectively called nucleons, are packed together tightly in a nucleus. With a radius of about 10−15 meters, a nucleus is quite small compared to the radius of the entire atom, which is about 10−10 meters. Nuclei are extremely dense compared to bulk matter, averaging 1.8 × 1014 grams per cubic centimeter. If the earth’s density were equal to the average nuclear density, the earth’s radius would be only about 200 meters.
To hold positively charged protons together...
23.3K
RNA Stability01:53

RNA Stability

35.7K
Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
35.7K
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

31.3K
Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
31.3K

You might also read

Related Articles

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

Sort by
Same author

Robust discovery of mutational signatures using power posteriors.

PLoS computational biology·2026
Same author

Sequential Gibbs posteriors with applications to principal component analysis.

Biometrika·2026
Same author

Local graph estimation with pathwise false discovery control.

Nature communications·2026
Same author

Reproducible parameter inference using bagged posteriors.

Electronic journal of statistics·2025
Same author

Model-based dimensionality reduction for single-cell RNA-seq using generalized bilinear models.

Biostatistics (Oxford, England)·2025
Same author

Nonparametric IPSS: fast, flexible feature selection with false discovery control.

Bioinformatics (Oxford, England)·2025
Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026
Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026
Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026
Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026
Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026
Same journal

SMART-MC: Characterizing the Dynamics of Multiple Sclerosis Therapy Transitions Using a Covariate-Based Markov Model.

Journal of the American Statistical Association·2026
See all related articles
  1. Home
  3. Integrated Path Stability Selection.
  1. Home
  3. Integrated Path Stability Selection.

Related Experiment Video

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

13.1K

Integrated path stability selection.

Omar Melikechi1, Jeffrey W Miller1

  • 1Department of Biostatistics, Harvard T.H. Chan School of Public Health.

Journal of the American Statistical Association
|February 2, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a novel stability selection method that integrates stability paths, significantly improving feature selection by yielding stronger false positive bounds and selecting more true positives without increased computational cost.

Keywords:
Bootstraperror controlfeature selectionresamplingvariable selection

More Related Videos

Foraging Path-length Protocol for Drosophila melanogaster Larvae
07:26

Foraging Path-length Protocol for Drosophila melanogaster Larvae

Published on: April 23, 2016

9.9K
CRISPR-Cas9-based Genome Engineering to Generate Jurkat Reporter Models for HIV-1 Infection with Selected Proviral Integration Sites
14:27

CRISPR-Cas9-based Genome Engineering to Generate Jurkat Reporter Models for HIV-1 Infection with Selected Proviral Integration Sites

Published on: November 14, 2018

10.3K

Related Experiment Videos

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

13.1K
Foraging Path-length Protocol for Drosophila melanogaster Larvae
07:26

Foraging Path-length Protocol for Drosophila melanogaster Larvae

Published on: April 23, 2016

9.9K
CRISPR-Cas9-based Genome Engineering to Generate Jurkat Reporter Models for HIV-1 Infection with Selected Proviral Integration Sites
14:27

CRISPR-Cas9-based Genome Engineering to Generate Jurkat Reporter Models for HIV-1 Infection with Selected Proviral Integration Sites

Published on: November 14, 2018

10.3K

Area of Science:

  • Statistical Learning
  • Bioinformatics
  • Computational Biology

Background:

  • Stability selection is a key technique for enhancing feature selection algorithms.
  • It offers theoretical bounds on expected false positives (E(FP)) for practical control.
  • Current methods often select limited features due to loose E(FP) bounds.

Purpose of the Study:

  • To develop a novel stability selection approach.
  • To achieve stronger upper bounds on E(FP) for improved feature selection.
  • To increase the number of true positives identified without compromising false positive control.

Main Methods:

  • Introduced a new stability selection approach by integrating stability paths instead of maximizing over them.
  • The method's computational complexity was analyzed and compared to existing algorithms.
  • Applied the novel method to simulations and real-world cancer study data.

    • Main Results:

    • The novel approach yields significantly stronger upper bounds on E(FP) compared to previous methods.
    • This leads to a substantial increase in true positives for a given E(FP) target.
    • The method demonstrated comparable computational efficiency to the original stability selection.

    Conclusions:

    • The integrated stability path approach offers a more effective strategy for feature selection.
    • This method enhances the performance of stability selection by improving false positive control and increasing true positive identification.
    • The approach is validated through simulations and its application in cancer genomics research.