Related Experiment Video
Updated: Feb 3, 2026

08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
16.5K
A Non-neutral Origin for Error Minimization in the Origin of the Genetic Code
1Early Evolution of Life Laboratory, Institute of Biosciences and Bioresources, CNR, Via P. Castellino, 111, 80131, Naples, Italy. massimodigiulio1952@gmail.com.
Journal of Molecular Evolution
|October 27, 2018
Summary
The origin of the genetic code
Area of Science:
- Evolutionary biology
- Molecular biology
- Genetics
Background:
- Theories on the origin of the genetic code.
- Debate between neutralist and selectionist hypotheses.
- Massey's claim of neutral origin for genetic code error minimization.
Related Concept Videos
Cancers Originate from Somatic Mutations in a Single Cell
14.9K
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
14.9K
Types of Errors: Detection and Minimization
11.4K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
11.4K
lncRNA - Long Non-coding RNAs
9.9K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
9.9K
What is Population Genetics?
64.7K
A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
64.7K
What is Genetic Engineering?
80.2K
Overview
80.2K
Systematic Error: Methodological and Sampling Errors
11.0K
In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
11.0K

