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And whatever I do will become forever what I've done.Wislawa Szymborskadon't rehearsemore quotes

DNA on 10th — street art, wayfinding and font


language + fiction

Dark Matter of the English Language—the unwords

Words are easy, like the wind;
Faithful friends are hard to find.
—William Shakespeare

unfeelings

Somedays it's hard to know what you feel.

Maybe it's because you don't have a word for it yet.

Did that flight leave you quacy because of the kadful food? Next time, you should be more infulic and insist on an upgrade.

I like my friends both kessive and wanric, which I find to provide a nice balance. I don't generally like those who are sadry or tamty.

If this makes you weable, keep it to yourself.

Below are the alphabetically first 5–12 letter single-word unanimals for each letter. In some cases, no names of a given length were generated for a given letter.

—5—
aabye
aacec
baagd
bacac
caane
caary
daagy
daany
eabed
eable
faary
faaty
gaaly
gaany
haady
haced
iaded
iaden
jahed
jamid
kebed
kecig
laasy
labed
machy
maded
naavy
nabul
oated
obeed
pabed
pabey
qaaly
qafed
rabus
racin
saady
saany
taamy
tably
uadec
uaned
vaaty
vable
waady
waany
xated
xeany
yaced
yagre
zalil
zfust
—6—
aacang
aadare
bacint
badeny
caanoy
caaove
dabred
dacric
eaapte
eacomt
faaded
faalul
gaajly
gaaole
hacied
hadful
iadeve
iafhed
jadent
jadicy
kadful
kagful
laafil
laared
maaded
macfil
nabfle
nabime
oabenn
oadant
paaced
pacful
qacant
qacent
raadry
raatyd
saaded
saated
taaikl
tadeny
uacape
uadess
vaadyd
vaased
waapmy
wacful
xashed
xefric
yaefus
yaptec
zadful
zorted
—7—
aacinat
aaciwed
baadive
baatain
caalave
caamful
dabrned
dacefun
eaagate
eabnsed
faarirt
faathul
gacaved
gacgest
habived
haceful
iagerad
iamimed
jaative
jaceaul
kaiding
karefol
laatful
laching
maacful
maasful
naanhed
nabefus
oaadein
oablagy
paative
pabrecy
qaading
qabilgy
raading
raaehgy
saaempe
saaflen
taateng
tabsang
uabrant
uafcans
vaakive
vaasted
waadful
waaekly
xeiricy
xerting
yanaced
yannant
ziclatl
zipfred
—8—
aablined
aacfiled
bacigled
badessed
caabefol
caadepus
daatated
daceased
eaabided
eabllive
faaciwty
faanhyen
gaatited
gadeding
habateng
hacantic
iabliged
iabumled
jabonted
jacerous
karkefus
katiomat
labpinty
lacioest
maaniked
mabrathy
naaqated
nabheful
oablieed
oacemhed
paatefel
pachapte
qaaloved
qaeigued
rabenooy
rablnred
saafiled
saagluse
tacdeful
tacerate
uabhliac
uadenabe
vaadeful
vaatious
waathful
waberous
xeadliun
xeenated
yagdaned
yaolapte
zafrebus
zleefled
—9—
aacressed
aadeiaged
baaderaus
babefaled
caacitave
caafaligy
dacfirive
daenimast
eaadimate
eablagied
faadented
faarulhed
gacsitive
gagpalled
habuinate
hacenglic
iabuttant
iadelaced
jaadevieg
jacrucsid
kacergiag
kelrerous
laasivain
lachdysmy
mabuilive
macelomed
nabfiated
nabiovain
oablasted
oablatled
paacratky
paaikline
qaterated
qeatioped
rabomated
racastaon
sacedable
sacgented
taayhlive
tabelious
uabussing
uadenated
vaalenabe
vaashious
waadoemat
wabenated
xilretate
xiserompe
yamrictun
yamurhing
zlevenist
zonansicy
—10—
aachinated
aacrlacted
babralkant
baerkanped
caabiohant
caapenious
dacmulting
dagrutased
eacadageed
eadgitated
faagyerave
facimfelit
gaeomasine
gamheluted
hacopaglic
hadgensted
iaberanted
iacapoaged
jafapified
jamhelable
kameracive
karionaled
lachulated
lacisingfe
machklaved
madncgreen
nachinamed
nackeluted
oablaghang
oadamative
padhinated
padhuivien
qafeleased
qauolivive
raanttuled
rachimhive
sabplegted
sacitusiol
tacfuleked
tacpuented
uacricited
uafeitomed
vacticaled
vactinated
wacherlaty
wacinpefol
xantosored
xeangerted
yanilisive
yellahaged
zhiwufolad
zomiunable
—11—
aadiricated
aadofaagave
baminathais
banaterible
caamilavive
cabmiusated
damimatited
danklusicom
eadhiecated
eapriuhated
faatigomate
facantefuon
gaanhwelady
gadateroped
hacapigefel
hacngomrens
iadegeasiel
iafolorable
jargionafil
jerhuvessed
katterative
keranhiving
labwefusant
lacingresen
mabmantkrey
maciraleful
nabtowinned
nactupivied
oabemptaced
oanhissenac
padiwabtent
paexhufiond
qeeferenged
qeesetaeste
raadivisged
racfistaled
saasterheve
sabesatired
taesaglenhe
tamgurtined
uafurentful
uaoraverene
vacerslaons
vacimartatt
waadrwfaced
wacgertions
xingfolsent
yansictivac
yericishing
zosperusted
—12—
aafewserable
abdepeastiad
banokrariled
basigousated
caaperousais
caarimiasate
damismainabl
daninpicided
eaisderiured
eampaptitive
faadolenated
faadyrerosed
garmristeful
geajrefobled
hacnimisated
hadcomtanful
ianasioraled
ianhistecite
jadhitiraled
joicawiveful
kanclinneful
kintimageful
laemkovapole
lalerblessed
madenstetint
maichapfiled
naberitenhed
nactimivital
oafiwhililed
obeigonhawed
paerhomerate
paevimionape
qaoishaustus
qrecsipinted
racigatergec
ragrionative
saanhionable
sacgrocelous
taapmincoary
taforetisteg
ubforsiolate
ubnaterative
vaborlarxfol
vacupatenous
wacforstrove
wamtechevons
xursiwolated
yanthrlevous
yastituflesd

Here are all some lists with common suffixes

*acy abmacy baplacy clacy eghacy feacy geacy henacy iceacy jhacy leacy meacy ncacy ornacy peacy quacy reacy somacy taracy unpncacy veacy weacy

*aed abmenaed baribraed calyifaed deidonaed eeraed filicaed gearaed henisifaed icifaed jrabyaed lafaed meciupaed nasibaed odaed pevibaed ralaed sadyraed tarlifaed uduraed valaed warpuifaed yisivaed

*ant aadedenant babralkant caabiohant dalhant eaxant facagrant galhant hamtlihant iabuttant jepulant kesretant lanant macnant nactant oabtant pairant qacant ranntant sabsant tanjerant uabrant vagkant wasgimant yannant zontoghant

*anted aagranted cadanted deanted eadhanted fatanted hintanted iaberanted leanted manted nanted ocranted partanted recinanted samtanted tachanted unhanted vanted wisanted yononanted

*any abany brany ceany daany ecmeraany foany gaany heany iodany krany lorany memany nmany orcany puabrany reany saany tiany umamany veany waany xeany yrany

*ate aadiwenate bodenate cabriocate damtate eaadimate faesiosate ganaonate habuinate iasate kocaterate latlerate mapicuate naiclenate oagrenate paciciate qrate rarhenate sabnate tacerate uaoonate vasferate wacteruate xelate yinanate

*ated aachinated baiated caated daatated eaderated facated gaeated haoiated iacmatated jeated keinerated lachulated maminated naaqated oalforated padhinated qated rabomated saated taidated uadenated vactinated wabenated xated yedeated

*ble aasable banible caceable damerable eable fagilable garable hafelible ibepapible jamhelable kiballible lable malable naenable oarhawable pable qafable raconable sablable tacsble uatharible vablable wacerable zomiunable

*ed aablined babefaled caagimed daatated eaabided faaded gaared habived iaberanted jabonted karionaled laared maaded naanhed oablasted paaced qaaloved raanttuled saaded tacfuleked uacricited vaased waanked xantosored yaced zimed

*ful aanful badeful caamful dadhful eacreful faapsful gacful haceful iatful jadeful kadful laatful maacful nabheful oanelful pacful qaitful raasful sabmeful tacdeful uasanful vaadeful waadful yenteful zadful

*gy abeegy bengy caafaligy daagy eubagy fantrbangy gengy halkagy inalgy jangy larpurgy mancracgy ncangy oablagy pagigy qabilgy raaehgy sadhargy tarpiwekgy ulergy vactongy wacikgy

*hed abmonhed bailhed caihed damurhed eafliched faarulhed galhed halowhed iafhed jahed kroufhed lemashed macithed naanhed oacemhed pached qeihed ralerhed sached tamhed ubmarhed vacihed wanished xashed yisathed

*ic aanomic bestic cabpulic dacric eafmic faatic galfic hacantic iavicatic jeoloouaic kapfic lacic maastic nameic oamaspic panatic qlatic ragburic saavicic talic uamericic vakic wacic xefric yassic

*ied aasivied banipatied cabrafied daomipied eablagied feafied gapatgied hacied iasirfied jafapified kolpiried lelrified mandumried napied obentified pagied qoied radied sabied taied udracied veatofied walied yasrified

*ive aastessive baadive caavive dacfirive eabllive fafresvive gacsitive hacfive iasive jaative kameracive lactive mabuilive nadvosive oadamative paative qasative racensive saanive taayhlive uafunitive vaakive wadotive xipilivive yanilisive zonixive

*lic acfulic borilic cabpulic deseelic enblic ferlic gearlic hacenglic infulic jilolic lecablic macablic nelalic ocpalrlic pealic qllic rastilic sanmacelic talic ulnataclic valic wartipilic

*ous abfsious banious caapenious dahilious ecdiadaous facious ganerous hacious iarepsious jacerous kelrerous laiwhacous madious nacelous oaperous pactious qarerous ralous saarous tabelious uagensious vaashious waberous xoodous yasious zowerlrous

*ric abmaric camric dacric ecjaaric faeric gesteric hararic icoeric juric leric mameric necric oncaric paric qoric ragburic sadeuric talric unisteric varic wanric xefric

*ry afpomery bikykury caary danery eipiry faary gaary hacry icary jeary kovary lantry magery naiwory obsery paegry qaulary raadry sadry tacuory uanabry vacalry waary xeary yincalry

*ty ablanty bamty cagnty dastimty eadnty faaciwty gakaty harty ilnpatty jerenty kagity labpinty maghenty nanty oblenty paduevaty qearty racternty sacty tamtonty uanaty vaaty wacherlaty xinty yolety zonturty

VIEW ALL

news + thoughts

Hola Mundo Cover

Sat 21-09-2019

My cover design for Hola Mundo by Hannah Fry. Published by Blackie Books.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Hola Mundo by Hannah Fry. Cover design is based on my 2013 `\pi` day art. (read)

Curious how the design was created? Read the full details.

Markov Chains

Tue 30-07-2019

You can look back there to explain things,
but the explanation disappears.
You'll never find it there.
Things are not explained by the past.
They're explained by what happens now.
—Alan Watts

A Markov chain is a probabilistic model that is used to model how a system changes over time as a series of transitions between states. Each transition is assigned a probability that defines the chance of the system changing from one state to another.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Markov Chains. (read)

Together with the states, these transitions probabilities define a stochastic model with the Markov property: transition probabilities only depend on the current state—the future is independent of the past if the present is known.

Once the transition probabilities are defined in matrix form, it is easy to predict the distribution of future states of the system. We cover concepts of aperiodicity, irreducibility, limiting and stationary distributions and absorption.

This column is the first part of a series and pairs particularly well with Alan Watts and Blond:ish.

Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Markov Chains. Nature Methods 16:663–664.

1-bit zoomable gigapixel maps of Moon, Solar System and Sky

Mon 22-07-2019

Places to go and nobody to see.

Exquisitely detailed maps of places on the Moon, comets and asteroids in the Solar System and stars, deep-sky objects and exoplanets in the northern and southern sky. All maps are zoomable.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
3.6 gigapixel map of the near side of the Moon, annotated with 6,733. (details)
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
100 megapixel and 10 gigapixel map of the Solar System on 20 July 2019, annotated with 758k asteroids, 1.3k comets and all planets and satellites. (details)
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
100 megapixle and 10 gigapixel map of the Northern Celestial Hemisphere, annotated with 44 million stars, 74,000 deep-sky objects and 3,000 exoplanets. (details)
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
100 megapixle and 10 gigapixel map of the Southern Celestial Hemisphere, annotated with 69 million stars, 88,000 deep-sky objects and 1000 exoplanets. (details)

Quantile regression

Sat 01-06-2019
Quantile regression robustly estimates the typical and extreme values of a response.

Quantile regression explores the effect of one or more predictors on quantiles of the response. It can answer questions such as "What is the weight of 90% of individuals of a given height?"

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Quantile regression. (read)

Unlike in traditional mean regression methods, no assumptions about the distribution of the response are required, which makes it practical, robust and amenable to skewed distributions.

Quantile regression is also very useful when extremes are interesting or when the response variance varies with the predictors.

Das, K., Krzywinski, M. & Altman, N. (2019) Points of significance: Quantile regression. Nature Methods 16:451–452.

Background reading

Altman, N. & Krzywinski, M. (2015) Points of significance: Simple linear regression. Nature Methods 12:999–1000.

Analyzing outliers: Robust methods to the rescue

Sat 30-03-2019
Robust regression generates more reliable estimates by detecting and downweighting outliers.

Outliers can degrade the fit of linear regression models when the estimation is performed using the ordinary least squares. The impact of outliers can be mitigated with methods that provide robust inference and greater reliability in the presence of anomalous values.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Analyzing outliers: Robust methods to the rescue. (read)

We discuss MM-estimation and show how it can be used to keep your fitting sane and reliable.

Greco, L., Luta, G., Krzywinski, M. & Altman, N. (2019) Points of significance: Analyzing outliers: Robust methods to the rescue. Nature Methods 16:275–276.

Background reading

Altman, N. & Krzywinski, M. (2016) Points of significance: Analyzing outliers: Influential or nuisance. Nature Methods 13:281–282.

Two-level factorial experiments

Fri 22-03-2019
To find which experimental factors have an effect, simultaneously examine the difference between the high and low levels of each.

Two-level factorial experiments, in which all combinations of multiple factor levels are used, efficiently estimate factor effects and detect interactions—desirable statistical qualities that can provide deep insight into a system.

They offer two benefits over the widely used one-factor-at-a-time (OFAT) experiments: efficiency and ability to detect interactions.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Two-level factorial experiments. (read)

Since the number of factor combinations can quickly increase, one approach is to model only some of the factorial effects using empirically-validated assumptions of effect sparsity and effect hierarchy. Effect sparsity tells us that in factorial experiments most of the factorial terms are likely to be unimportant. Effect hierarchy tells us that low-order terms (e.g. main effects) tend to be larger than higher-order terms (e.g. two-factor or three-factor interactions).

Smucker, B., Krzywinski, M. & Altman, N. (2019) Points of significance: Two-level factorial experiments Nature Methods 16:211–212.

Background reading

Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments.. Nature Methods 11:597–598.