Answer: 6
Explanation:
This is because the Met and Trp are coded by one codon, Cys is coded by two different codons, and Stop is encoded by three different codons. Therefor, 2x3=6.
Answer:
C
Explanation:
Positive natural selection, or the tendency of beneficial traits to increase in prevalence (frequency) in a population, is the driving force behind adaptive evolution. ... At the molecular level, selection occurs when a particular DNA variant becomes more common because of its effect on the organisms that carry it.
The triceps brachii muscle attaches to the olecranon process of the ulna crossing the posterior side of the elbow joint. that will allow the triceps to be an <u>Extensor </u>of the elbow joint.
- Directly affected is the common extensor tendon, which arises from the lateral epicondyle of the elbow.
- The common extensor tendon is made up of the extensor carpi radialis brevis (ECRB) and longus, extensor digitorum, extensor digiti minimi, and extensor carpi ulnaris.
- The main elbow flexors are the biceps brachii, brachialis, and brachioradialis.
- The main elbow extensor is the triceps brachii. Although it is also believed that the anconeus contributes to elbow extension.
- The proximal articular region of the ulna is called the olecranon. It creates the larger sigmoid notch, which articulates with the humerus to allow for elbow flexion and extension, together with the coronoid process.
- The main point of attachment for the forearm's extensor muscles is the common extensor tendon. This promotes forearm supination and allows finger extension.
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the causes of most of them are unknown. Some birth defects are considered to be physical, while others are thought of as functional. Physical birth defects result in the malformation.
Answer:
In information theory, entropy is a measure of uncertainty in a random variable. In this context, the term refers to Shannon's entropy, which quantifies the expected value of the information contained in a message.
Explanation:
The entropy defined by Shannon, referring to the theory of information, refers to the average amount of information contained in a random (psychological) variable or, in particular, a binary transmission source. The information that provides a certain value, xi, of a discrete random variable X, is defined as:
I (xi) = log2 (1 / p (xi))
whose unit is the bit if the logarithm is used in base 2 (for example, when the natural or natural logarithm is used, we speak of nats).
The entropy or average information of the discrete random variable, X, is determined as the average information of the set of discrete values that can be adopted (also measured in bits):
H (x) = Σip (xi) • log2 (1 / p (xi))
In addition to its definition and study, Shannon demonstrated analytically that entropy is the maximum limit to which a source can be compressed without any loss of information.
