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

Optimization Problems01:26

Optimization Problems

78
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
78
Trimmed Mean01:10

Trimmed Mean

3.4K
While measuring the mean of a data set, care needs to be taken when associating the mean to its central tendency. The same goes for the arithmetic mean, the geometric mean, or the harmonic mean. This is because the presence of a single outlier data value can significantly affect the mean. That is, the mean is sensitive to fluctuations in the data set.
Although certain measures of central tendency are not sensitive to outliers, there are alternative versions of the mean that get around the...
3.4K
Next-generation Sequencing03:00

Next-generation Sequencing

98.7K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
98.7K
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

11.9K
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
11.9K
Optimal Foraging00:48

Optimal Foraging

13.9K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
13.9K
Block Diagram Reduction01:22

Block Diagram Reduction

567
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
567

You might also read

Related Articles

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

Sort by
Same author

Comparison between molecular and histological IDH-wild-type glioblastoma and extensive subgroup analysis of IDH-wild-type astrocytic tumors without genomic glioblastoma-defining alterations.

Journal of neuro-oncology·2026
Same author

Fast barcode calling based on <i>k</i>-mer distances.

PNAS nexus·2026
Same author

Evolutionary transcriptomics unveils rapid changes of gene expression patterns in flowering plants.

Cell·2026
Same author

Inferring binding specificities of human transcription factors with the wisdom of crowds.

bioRxiv : the preprint server for biology·2025
Same author

Cross-platform motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors.

Communications biology·2025
Same author

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors.

bioRxiv : the preprint server for biology·2024
Same journal

circ2DGNN: circRNA-Disease Association Prediction via Transformer-Based Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Hierarchical Hypergraph Learning in Association- Weighted Heterogeneous Network for miRNA- Disease Association Identification.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Discriminative Domain Adaption Network for Simultaneously Removing Batch Effects and Annotating Cell Types in Single-Cell RNA-Seq.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

MLW-BFECF: A Multi-Weighted Dynamic Cascade Forest Based on Bilinear Feature Extraction for Predicting the Stage of Kidney Renal Clear Cell Carcinoma on Multi-Modal Gene Data.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics·2024
Same journal

Generative Biomedical Event Extraction With Constrained Decoding Strategy.

IEEE/ACM transactions on computational biology and bioinformatics·2024
See all related articles

Related Experiment Video

Updated: Feb 9, 2026

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
07:30

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

12.8K

Optimal Block-Based Trimming for Next Generation Sequencing.

Ivo Hedtke, Ioana Lemnian, Ivo Grosse

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |April 25, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces optimized algorithms for next-generation sequencing (NGS) read trimming, improving data analysis by better preserving valuable sequence data compared to traditional methods.

    More Related Videos

    Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
    12:33

    Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

    Published on: July 28, 2017

    13.5K
    Targeted DNA Methylation Analysis by Next-generation Sequencing
    08:38

    Targeted DNA Methylation Analysis by Next-generation Sequencing

    Published on: February 24, 2015

    38.0K

    Related Experiment Videos

    Last Updated: Feb 9, 2026

    Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
    07:30

    Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

    Published on: June 8, 2020

    12.8K
    Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
    12:33

    Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

    Published on: July 28, 2017

    13.5K
    Targeted DNA Methylation Analysis by Next-generation Sequencing
    08:38

    Targeted DNA Methylation Analysis by Next-generation Sequencing

    Published on: February 24, 2015

    38.0K

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Next-generation sequencing (NGS) data analysis requires read trimming as a crucial preprocessing step.
    • Traditional read trimming methods are often heuristic and lack rigorous algorithmic foundations.
    • Algorithmic approaches to read trimming have been historically underdeveloped.

    Purpose of the Study:

    • To formulate and address optimization problems for block-based read trimming in NGS data.
    • To investigate the computational complexity and approximability of these trimming problems.
    • To develop efficient algorithms for optimized read trimming, considering practical data characteristics.

    Main Methods:

    • Formulation of three NP-hard optimization problems for block-based read trimming.
    • Investigation of the approximability of these NP-hard problems.
    • Development of polynomial-time algorithms for relaxed trimming problems, incorporating heuristics and parallelization.
    • Application and validation of algorithms on diverse NGS datasets.

    Main Results:

    • The proposed relaxed problems yield solutions that typically satisfy the omitted constraints.
    • Optimized block trimming algorithms generally result in a higher number of retained (untrimmed) bases compared to heuristic methods.
    • The effectiveness of the optimized algorithms is consistent across various species, sequencers, and read lengths.
    • Findings are generalizable to alternative objective functions beyond maximizing untrimmed bases.

    Conclusions:

    • Efficient and optimized algorithms can significantly improve the read trimming process in NGS data analysis.
    • The developed methods offer a more effective approach to preserving sequence data quality and quantity.
    • This work provides a strong algorithmic foundation for a fundamental step in bioinformatics.