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🔗 Biology 🔗 Genetics 🔗 Computational Biology 🔗 Evolutionary biology 🔗 Human Genetic History

The last universal common ancestor (LUCA), also called the last universal ancestor (LUA), or concestor, is the most recent population of organisms from which all organisms now living on Earth have a common descent, the most recent common ancestor of all current life on Earth. (A related concept is that of progenote.) LUCA is not thought to be the first life on Earth but only one of many early organisms, all the others becoming extinct.

While there is no specific fossil evidence of LUCA, it can be studied by comparing the genomes of all modern organisms, its descendants. By this means, a 2016 study identified a set of 355 genes most likely to have been present in LUCA. (However, some of those genes could have developed later, then spread universally by horizontal gene transfer between archaea and bacteria.) The genes describe a complex life form with many co-adapted features, including transcription and translation mechanisms to convert information from DNA to RNA to proteins. The study concluded that the LUCA probably lived in the high-temperature water of deep sea vents near ocean-floor magma flows.

Studies from 2000 to 2018 have suggested an increasingly ancient time for LUCA. In 2000, estimations suggested LUCA existed 3.5 to 3.8 billion years ago in the Paleoarchean era, a few hundred million years after the earliest fossil evidence of life, for which there are several candidates ranging in age from 3.48 to 4.28 billion years ago. A 2018 study from the University of Bristol, applying a molecular clock model, places the LUCA shortly after 4.5 billion years ago, within the Hadean.

Charles Darwin first proposed the theory of universal common descent through an evolutionary process in his book On the Origin of Species in 1859: "Therefore I should infer from analogy that probably all the organic beings which have ever lived on this earth have descended from some one primordial form, into which life was first breathed." Later biologists have separated the problem of the origin of life from that of the LUCA.

🔗 Computing 🔗 Statistics 🔗 Computational Biology

The following is a list of algorithms along with one-line descriptions for each.

🔗 Viruses 🔗 Statistics 🔗 Computational Biology

A super-spreader is an unusually contagious organism infected with a disease. In context of a human-borne illness, a super-spreader is an individual who is more likely to infect others, compared with a typical infected person. Such super-spreaders are of particular concern in epidemiology.

Some cases of super-spreading conform to the 80/20 rule, where approximately 20% of infected individuals are responsible for 80% of transmissions, although super-spreading can still be said to occur when super-spreaders account for a higher or lower percentage of transmissions. In epidemics with super-spreading, the majority of individuals infect relatively few secondary contacts.

Super-spreading events are shaped by multiple factors including a decline in herd immunity, nosocomial infections, virulence, viral load, misdiagnosis, airflow dynamics, immune suppression, and co-infection with another pathogen.

🔗 Computer science 🔗 Molecular and Cell Biology 🔗 Computational Biology

The Needleman–Wunsch algorithm is an algorithm used in bioinformatics to align protein or nucleotide sequences. It was one of the first applications of dynamic programming to compare biological sequences. The algorithm was developed by Saul B. Needleman and Christian D. Wunsch and published in 1970. The algorithm essentially divides a large problem (e.g. the full sequence) into a series of smaller problems, and it uses the solutions to the smaller problems to find an optimal solution to the larger problem. It is also sometimes referred to as the optimal matching algorithm and the global alignment technique. The Needleman–Wunsch algorithm is still widely used for optimal global alignment, particularly when the quality of the global alignment is of the utmost importance. The algorithm assigns a score to every possible alignment, and the purpose of the algorithm is to find all possible alignments having the highest score.