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Related Concept Videos

Prediction Intervals01:03

Prediction Intervals

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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
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Structural Joints: Synovial Joints01:16

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Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Structural Joints: Fibrous Joints01:03

Structural Joints: Fibrous Joints

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
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Structural Joints: Cartilaginous Joints01:17

Structural Joints: Cartilaginous Joints

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
There are two types of cartilaginous joints:
Synchondrosis
A synchondrosis ("joined by cartilage") is a cartilaginous joint where bones are connected by hyaline cartilage. Synchondrosis may be temporary...
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Related Experiment Video

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Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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JOA: Joint Overlap Analysis of multiple genomic interval sets.

Burçak Otlu1, Tolga Can2

  • 1Department of Computer Engineering, Middle East Technical University, Ankara, 06800, Turkey. burcak@ceng.metu.edu.tr.

BMC Bioinformatics
|March 10, 2019
PubMed
Summary

Joint Overlap Analysis (JOA) offers efficient parallel processing for genomic interval intersection, overcoming limitations of existing tools. This novel approach handles nested and unsorted intervals across multiple datasets, improving genomic data analysis.

Keywords:
Genome analysisGenomic interval intersectionIndexed segment tree forestInterval intersectionInterval overlapJoint overlap analysisSegment treeSpace partitioning algorithms

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Next-generation sequencing (NGS) generates vast genomic data, necessitating efficient analysis tools.
  • Genomic interval intersection is a common but complex operation on heterogeneous genomic datasets.
  • Existing tools often have limitations, such as disallowing nested intervals or requiring sorted input.

Purpose of the Study:

  • To develop a novel parallel algorithm for intersecting multiple genomic interval sets without constraints.
  • To introduce a new data structure, the indexed segment tree forest (ISTF), for efficient interval analysis.
  • To create a user-friendly tool, Joint Overlap Analysis (JOA), for versatile genomic interval intersection.

Main Methods:

  • Proposed segment tree (ST) and indexed segment tree forest (ISTF) based parallel algorithms.
  • Developed the Joint Overlap Analysis (JOA) tool implementing these novel methods.
  • Designed construction and search algorithms for the ISTF data structure.

Main Results:

  • JOA successfully intersects multiple genomic interval sets, accommodating nested and unsorted intervals.
  • The ISTF data structure provides an efficient method for parallel genomic interval intersection.
  • JOA demonstrates comparable execution times to existing tools while offering greater flexibility.

Conclusions:

  • JOA, implemented in Java using the fork/join framework, enables efficient parallel processing.
  • Both ST and ISTF methods within JOA show comparable performance in execution time and memory usage.
  • JOA offers a flexible and efficient solution for complex genomic interval intersection tasks, with performance scaling with increased processors.