Is breast cancer bimodal?

Breast cancers were best characterized by bimodal age distribution at diagnosis with incidence peaks near 45 and 65 years, regardless of molecular characteristics. However, proportional composition of early-onset and late-onset age distributions varied by molecular and genomic characteristics.

What is bimodal expression?

Bimodal gene expression (the distribution of gene products that has two maxima) is a cause of phenotypic diversity in genetically identical cell populations, and it is critical for population survival in a fluctuating environment (1–4).

Can a normal distribution be bimodal?

A mixture of two normal distributions with equal standard deviations is bimodal only if their means differ by at least twice the common standard deviation.

Can a distribution have two means?

Multimodal Distributions The “mode” in bimodal distribution means a local maximum in a chart (i.e. a local mode). The two terms actually mean the same thing, as the most commonly found item in a data set will have a peak.

What is an example of bimodal distribution?

Often bimodal distributions occur because of some underlying phenomena. For example, the number of customers who visit a restaurant each hour follows a bimodal distribution since people tend to eat out during two distinct times: lunch and dinner. This underlying human behavior is what causes the bimodal distribution.

What type of distribution is bimodal?

A bimodal distribution has two peaks (hence the name, bimodal). They are usually a mixture of two unique unimodal (only one peak, for example a normal or Poisson distribution) distributions, relying on two distributed variables X and Y, with a mixture coefficient α.

What causes bimodal distribution?

What may be the reason for the bimodal distribution?

Is bimodal distribution considered normal?

Is bimodal normal?

A mixture of two normal distributions with equal standard deviations is bimodal only if their means differ by at least twice the common standard deviation.”

What is bimodal example?

Bimodal literally means “two modes” and is typically used to describe distributions of values that have two centers. For example, the distribution of heights in a sample of adults might have two peaks, one for women and one for men. Browse Other Glossary Entries.

How do you analyze a bimodal distribution?

A better way to analyze and interpret bimodal distributions is to simply break the data into two separate groups, then analyze the center and the spread for each group. For example, we may break up the exam scores into “low scores” and “high scores” and then find the mean and standard deviation for each group.

What does bimodal look like?

Bimodal: A bimodal shape, shown below, has two peaks. This shape may show that the data has come from two different systems. If this shape occurs, the two sources should be separated and analyzed separately. Skewed right: Some histograms will show a skewed distribution to the right, as shown below.

What is the reason for bimodal distribution?

Q. What does a Bimodal Distribution tell you? You’ve got two peaks of data, which usually indicates you’ve got two different groups. For example, exam scores tend to be normally distributed with a single peak.

What is bimodality of gene expression in breast cancer?

We described the phenomenon of bimodality of gene expression in breast cancer and grouping of the bimodal genes into «close neighbor» groups. The sets of bimodal genes are non-random; they are enriched in disease markers and targets and tend to form functionally related groups with synchronised expression.

What do gene expression patterns tell us about breast cancer tumors?

Medical Sciences Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

What is a bimodal gene distribution?

Bimodal genes feature a distribution with two distinct peaks (maximal signals) (Fig 1B ). For each gene, we can set up a distinguishing expression value such that the signals lower than this value correspond to the lower peak in the bimodal distribution, and the signals higher than this value correspond to the higher peak.

Is ‘bimodality’ a general phenomenon?

We show that “bimodality” is a general phenomenon (at least for breast cancer), independent of a microarray platform and clinical phenotype (patient cohort). Bimodality is intrinsically associated with physiological states of the system, such as cancer vs. normal.