Editing Log-normal distribution (section)

=== Biology and medicine ===

* Measures of size of living tissue (length, skin area, weight).<ref>{{cite book | last = Huxley | first = Julian S. | year = 1932 | title = Problems of relative growth | publisher = London | oclc = 476909537 | isbn = 978-0-486-61114-3 }}</ref>
* Incubation period of diseases.<ref>Sartwell, Philip E. "The distribution of incubation periods of infectious disease." ''American journal of hygiene'' 51 (1950): 310–318.</ref>
* Diameters of banana leaf spots, powdery mildew on barley.<ref name=":0" />
* For highly communicable epidemics, such as SARS in 2003, if public intervention control policies are involved, the number of hospitalized cases is shown to satisfy the log-normal distribution with no free parameters if an entropy is assumed and the standard deviation is determined by the principle of maximum rate of [[entropy production]].<ref>{{cite journal | last1 = S. K. Chan | first1 = Jennifer | last2 = Yu | first2 = Philip L. H. | title = Modelling SARS data using threshold geometric process | journal = Statistics in Medicine | date = 2006 | volume = 25 | issue = 11 | pages = 1826–1839 | doi = 10.1002/sim.2376 | pmid = 16345017 | s2cid = 46599163 }}</ref>
* The length of inert appendages (hair, claws, nails, teeth) of biological specimens, in the direction of growth.{{Citation needed | date = February 2011}}
* The normalised RNA-Seq readcount for any genomic region can be well approximated by log-normal distribution.
* The [[Pacific Biosciences|PacBio]] sequencing read length follows a log-normal distribution.<ref>{{Cite journal | last1 = Ono | first1 = Yukiteru | last2 = Asai | first2 = Kiyoshi | last3 = Hamada | first3 = Michiaki | date = 2013-01-01 | title = PBSIM: PacBio reads simulator—toward accurate genome assembly | url = https://academic.oup.com/bioinformatics/article/29/1/119/273243 | journal = Bioinformatics | language = en | volume = 29 | issue = 1 | pages = 119–121 | doi = 10.1093/bioinformatics/bts649 | pmid = 23129296 | issn = 1367-4803 | doi-access = free}}</ref>
* Certain physiological measurements, such as blood pressure of adult humans (after separation on male/female subpopulations).<ref>{{cite journal | last = Makuch | first = Robert W. | author2 = D.H. Freeman | author3 = M.F. Johnson | title = Justification for the lognormal distribution as a model for blood pressure | journal = Journal of Chronic Diseases | year = 1979 | volume = 32 | issue = 3 | pages = 245–250 | doi = 10.1016/0021-9681(79)90070-5 | pmid = 429469 }}</ref>
*Several [[Pharmacokinetics|pharmacokinetic]] variables, such as [[Cmax (pharmacology)|C<sub>max</sub>]], [[Biological half-life|elimination half-life]] and the [[elimination rate constant]].<ref>{{Cite journal | last1 = Lacey | first1 = L. F. | last2 = Keene | first2 = O. N. | last3 = Pritchard | first3 = J. F. | last4 = Bye | first4 = A. | date = 1997-01-01 | title = Common noncompartmental pharmacokinetic variables: are they normally or log-normally distributed? | url = https://www.tandfonline.com/doi/full/10.1080/10543409708835177 | journal = Journal of Biopharmaceutical Statistics | language = en | volume = 7 | issue = 1 | pages = 171–178 | doi = 10.1080/10543409708835177 | pmid = 9056596 | issn = 1054-3406}}</ref>
* In neuroscience, the distribution of firing rates across a population of neurons is often approximately log-normal. This has been first observed in the cortex and striatum <ref>{{Cite conference | last1 = Scheler | first1 = Gabriele | last2 = Schumann | first2 = Johann | title = Diversity and stability in neuronal output rates | conference = 36th Society for Neuroscience Meeting, Atlanta | date = 2006-10-08}}</ref> and later in hippocampus and entorhinal cortex,<ref>{{Cite journal | last1 = Mizuseki | first1 = Kenji | last2 = Buzsáki | first2 = György | date = 2013-09-12 | title = Preconfigured, skewed distribution of firing rates in the hippocampus and entorhinal cortex | journal = Cell Reports | volume = 4 | issue = 5 | pages = 1010–1021 | doi = 10.1016/j.celrep.2013.07.039 | issn = 2211-1247 | pmc = 3804159 | pmid = 23994479}}</ref> and elsewhere in the brain.<ref name=":4">{{Cite journal | last1 = Buzsáki | first1 = György | last2 = Mizuseki | first2 = Kenji | date = 2017-01-06 | title = The log-dynamic brain: how skewed distributions affect network operations | journal = Nature Reviews. Neuroscience | volume = 15 | issue = 4 | pages = 264–278 | doi = 10.1038/nrn3687 | issn = 1471-003X | pmc = 4051294 | pmid = 24569488}}</ref><ref>{{Cite journal | last1 = Wohrer | first1 = Adrien | last2 = Humphries | first2 = Mark D. | last3 = Machens | first3 = Christian K. | date = 2013-04-01 | title = Population-wide distributions of neural activity during perceptual decision-making | journal = Progress in Neurobiology | volume = 103 | pages = 156–193 | doi = 10.1016/j.pneurobio.2012.09.004 | issn = 1873-5118 | pmid = 23123501 | pmc = 5985929}}</ref> Also, intrinsic gain distributions and synaptic weight distributions appear to be log-normal<ref>{{Cite journal | last = Scheler | first = Gabriele | title = Logarithmic distributions prove that intrinsic learning is Hebbian | journal = F1000Research | doi = 10.12688/f1000research.12130.2 | date = 2017-07-28 | pmid = 29071065 | volume = 6 | pmc = 5639933 | page = 1222 | doi-access = free }}</ref> as well.
*Neuron densities in the cerebral cortex, due to the noisy cell division process during neurodevelopment.<ref>{{cite journal | last1 = Morales-Gregorio | first1 = Aitor | last2 = van Meegen | first2 = Alexander | last3 = van Albada | first3 = Sacha | year = 2023 | title = Ubiquitous lognormal distribution of neuron densities in mammalian cerebral cortex | journal = Cerebral Cortex | volume = 33 | issue = 16 | pages = 9439–9449 | doi = 10.1093/cercor/bhad160 | pmid = 37409647 | pmc = 10438924 }}</ref>
*In operating-rooms management, the distribution of [[Predictive methods for surgery duration|surgery duration]].
*In the size of avalanches of fractures in the cytoskeleton of living cells, showing log-normal distributions, with significantly higher size in cancer cells than healthy ones.<ref>{{Cite journal | last1 = Polizzi | first1 = Stefano | last2 = Laperrousaz | first2 = Bastien | last3 = Perez-Reche | first3 = Francisco J | last4 = Nicolini | first4 = Franck E | last5 = Satta | first5 = Véronique Maguer | last6 = Arneodo | first6 = Alain | last7 = Argoul | first7 = Françoise | date = 2018-05-29 | title = A minimal rupture cascade model for living cell plasticity | url = https://iopscience.iop.org/article/10.1088/1367-2630/aac3c7 | journal = New Journal of Physics | volume = 20 | issue = 5 | pages = 053057 | doi = 10.1088/1367-2630/aac3c7 | bibcode = 2018NJPh...20e3057P | issn = 1367-2630 | hdl = 2164/10561 |hdl-access = free }}</ref>