Python Programming for Biology: Bioinformatics and Beyond



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[Tim J. Stevens, Wayne Boucher] Python Programming

(computing):

Fundamental frequency



(signal processing):

Gamma correction



(graphics):

Garbage collection



(computing):

Gaussian distribution



(mathematics):

Gel electrophoresis



(molecular biology):

Gene (molecular



biology):

Describes a data structure that is fixed and cannot be modified

after creation, for example a tuple or frozen set in Python.

Sometimes called a subroutine, a function is part of a computer

program that represents an encapsulated set of commands in a

block that is separate from the main flow of the program, but

which may be invoked from different points within the program.

A function is usually written to perform a general operation on

an abstract set of inputs.

Representing a continuous mathematical function (which is

typically highly complex and/or unknown) for which some data

points are known, in an approximate way using a combination

of simpler functions that have been fitted to the data.

A frequency in the range of the recorded frequencies, which

might not be the true frequency of a signal because of aliasing

(see above).

The process of changing the brightness of an image using a

power law. This does not affect the black and white extremes of

brightness, but intermediate values are scaled to lighten or

darken an image, depending on the gamma value: above 1.0 will

darken and below 1.0 will lighten.

Freeing allocated computer memory that is no longer being

used.

Also called the normal distribution, a special continuous



probability distribution with a ‘bell’ shape that is determined by

its mean and standard deviation and that occurs in many

applications of statistics.

The process of separating dissolved molecules by passing them

through a gel substance using an electric current. Typically this

is done to separate the molecules according to their size or

electric charge.

The unit of inheritance in biological systems, which is formed

by a particular DNA sequence within the genome of an



Gene duplication

(molecular biology):

Generator (computing):

Genetic algorithm

(computing):

Genetic code (molecular



biology):

Genome (biology):

Genome build

(bioinformatics):

Geometric distribution



(mathematics):

organism. Genes are a persistent store of information and are

read to make functional RNA and protein molecules that control

an organism’s biochemistry.

The process of copying a gene inside a given genome.

Duplication arises from errors in DNA replication and from

mobile genetic elements (like viruses). The copying of a gene

allows for evolutionary diversification, as the two genes can

take on different roles as they diverge.

A memory-saving method for functions that give back a list, by

only returning each element in the list as it is needed, rather than

a full list.

An iterative optimisation method that seeks to find better

combinations of parameters by mimicking the way that a

population of genes change and are selected in evolution. The

algorithm involves a population of solutions to the problem

which are improved upon by mutation: small changes in

parameters, crossover; swapping large blocks of parameters and

then propagation of the ‘fittest’ solutions to the next round. This

is an alternative to Monte Carlo and simulated annealing

approaches.

The rules for translating DNA and RNA sequences into protein

sequences; for going from three adjacent nucleotide residues in

a codon (64 possibilities) to the 20 standard amino acids or a

sequence stop. A genetic code is specified by tRNA molecules

and the synthetase enzymes that associate a particular amino

acid to a particular codon. Animals have a slightly different

genetic code in the nucleus compared to their mitochondria.

The entirety of an organism’s (or cell’s) genetic information,

stored in its chromosomes as a sequence of nucleic acids

(generally DNA but RNA in some viruses).

The particular version of an assembled genome sequence, i.e.

the current state of sequence knowledge.

A discrete probability distribution that models how long it takes

to have a successful trial, where the probability of success for



Geometry management


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