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Related Concept Videos

Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
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Evolutionary Relationships through Genome Comparisons02:54

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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...
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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Estimating Population Standard Deviation01:26

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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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Speciation Rates

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Related Experiment Video

Updated: Dec 28, 2025

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles
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STELAR: a statistically consistent coalescent-based species tree estimation method by maximizing triplet consistency.

Mazharul Islam1, Kowshika Sarker1, Trisha Das1

  • 1Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1205, Bangladesh.

BMC Genomics
|February 11, 2020
PubMed
Summary

STELAR is a new, fast, and accurate method for species tree estimation using gene trees. It addresses challenges like incomplete lineage sorting (ILS) and scales well for large datasets, matching ASTRAL

Keywords:
Gene tree incongruenceIncomplete lineage sortingMulti-species coalescent processPhylogenomics

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Area of Science:

  • Phylogenomics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Species tree estimation often uses phylogenomic data from multiple genes.
  • Gene tree incongruence due to incomplete lineage sorting (ILS) complicates species tree inference.
  • Current methods like Maximum Likelihood and Bayesian MCMC struggle with scalability for large datasets.

Purpose of the Study:

  • To introduce STELAR (Species Tree Estimation by maximizing tripLet AgReement), a novel, statistically consistent, coalescent-based method for species tree estimation.
  • To address the limitations of existing methods in terms of speed, accuracy, and scalability.

Main Methods:

  • Formalized the constrained triplet consensus (CTC) problem.
  • Developed STELAR as an efficient dynamic programming solution to the CTC problem.
  • Evaluated STELAR against SuperTriplets, MP-EST, and ASTRAL using simulated and real biological datasets.

Main Results:

  • STELAR provides a statistically consistent species tree estimate under the multi-species coalescent (MSC) model.
  • STELAR demonstrates high accuracy and scalability.
  • STELAR matches the accuracy of ASTRAL and outperforms MP-EST and SuperTriplets.

Conclusions:

  • STELAR is a valuable and efficient technique for species tree estimation.
  • Theoretical and empirical evidence supports STELAR's utility with gene tree distributions.
  • The method effectively handles challenges posed by ILS in phylogenomic analyses.