iucr

commissions

principles
aperiodic crystals
biological macromolecules
charge, spin and momentum densities
crystal growth and characterization of materials
crystallographic computing
crystallographic nomenclature
crystallographic teaching
crystallography in art and cultural heritage
crystallography of materials
electron crystallography
high pressure
inorganic and mineral structures
international tables
journals
magnetic structures
mathematical and theoretical crystallography
neutron scattering
nmr crystallography
powder diffraction
small-angle scattering
structural chemistry
synchrotron and xfel radiation
xafs

congress

2020 iucr xxv
2017 iucr xxiv
2014 iucr xxiii
2011 iucr xxii
2008 iucr xxi
2005 iucr xx
2002 iucr xix
1999 iucr xviii
1996 iucr xvii
1993 iucr xvi
1990 iucr xv
1987 iucr xiv
1984 iucr xiii
1981 iucr xii
1978 iucr xi
1975 iucr x
1972 iucr ix
1969 iucr viii
1966 iucr vii
1963 iucr vi
1960 iucr v
1957 iucr iv
1954 iucr iii
1951 iucr ii
1948 iucr i

people

nobel prize

all
agre
anfinsen
barkla
boyer
w.h.bragg
w.l.bragg
brockhouse
de broglie
charpak
crick
curl
davisson
debye
deisenhofer
geim
de gennes
hauptman
hodgkin
huber
karle
karplus
kendrew
klug
kobilka
kornberg
kroto
laue
lefkowitz
levitt
lipscomb
mackinnon
michel
novoselov
pauling
perutz
ramakrishnan
roentgen
shechtman
shull
skou
smalley
steitz
sumner
thomson
walker
warshel
watson
wilkins
yonath

resources

commissions

aperiodic crystals
biological macromolecules
charge, spin and momentum densities
crystallographic computing
crystal growth and characterization of materials
crystallographic nomenclature
crystallographic teaching
crystallography in art and cultural heritage
crystallography of materials
electron crystallography
high pressure
inorganic and mineral structures
international tables
journals
magnetic structures
mathematical and theoretical crystallography
neutron scattering
nmr crystallography
powder diffraction
small-angle scattering
structural chemistry
synchrotron radiation
xafs

outreach

openlabs

calendar
Bruker OpenLab Cameroon
Rigaku OpenLab Bolivia
Bruker OpenLab Albania
Bruker OpenLab Uruguay 2
Rigaku OpenLab Cambodia 2
Bruker OpenLab Vietnam 2
Bruker OpenLab Senegal
PANalytical OpenLab Mexico 2
CCDC OpenLab Kenya
Bruker OpenLab Tunisia
Bruker OpenLab Algeria
PANalytical OpenLab Turkey
Bruker OpenLab Vietnam
Agilent OpenLab Hong Kong
PANalytical OpenLab Mexico
Rigaku OpenLab Colombia
grenoble-darmstadt
Agilent OpenLab Turkey
Bruker OpenLab Indonesia
Bruker OpenLab Uruguay
Rigaku OpenLab Cambodia
PANalytical OpenLab Ghana
Bruker OpenLab Morocco
Agilent OpenLab Argentina
Bruker OpenLab Pakistan

Compared with humans, computers have the capacity to solve problems at much greater speed. There are many problems, however, where computational speed alone is insufficient to find a correct or optimal solution, for example because the parameter “space” cannot be fully searched in a practical time. In contrast, the human mind can formulate expert knowledge specific for particular problems, providing a capacity to guide more efficient searches, although with more limited processing speed.

The power of the human contribution can be multiplied through the efforts of a greater number of individuals. The term `crowdsourcing', which combines the two domains of human and electronic computing, was coined in 2006 and since then has seen its definition broadened to a wide range of activities involving a network of people.

A challenging problem that might benefit from crowdsourcing is the phase problem in X-ray crystallography. Retrieving the phase information has plagued many scientists for decades when trying to determine the crystal structure of a sample.

In a diffraction experiment, the observed diffraction pattern allows measurement of the amplitudes of the reflection structure factors (as the square root of the intensities) but not their phases. The amplitudes and phases are both needed to reconstruct an electron-density map (by Fourier synthesis) so that a model of the crystallized molecule can be obtained.

There are a number of ways currently scientists try to solve the phase problem, all with varying degrees of success.

Regardless of the particular approach, most attacks on the phase problem can be viewed as having two sub-problems. One concerns how a high-dimensional space (*i.e.* of phases) can be efficiently searched, while the other concerns how a good solution can be recognized.

Crowdsourcing may be a route to solving these sub-problems [Jorda *et al.* (2014), *Acta Cryst.* D**70**, 1538-1548; doi:10.1107/S1399004714006427], here scientists have developed a game based on a genetic algorithm (a powerful search-optimization technique), where players control the selection mechanism during the evolutionary process (by recognising the good solutions). The algorithm starts from a population of “individuals”, in this case a map prepared from a random set of phases, and tries to cause the population to evolve towards individuals with better phases based on Darwinian survival of the fittest. Players apply their pattern-recognition capabilities to evaluate the electron-density maps generated from these sets of phases and to select the fittest individuals.

The game called *CrowdPhase* (http://www.crowdphase.com) was applied to two synthetic low-resolution phasing puzzles and it was shown that players could successfully obtain phase sets in the 30 degree phase error range and corresponding molecular envelopes showing agreement with the low-resolution models.

Successful preliminary studies suggest that with further development the crowdsourcing approach could fill a gap in current crystallographic methods by making it possible to extract meaningful information in cases where limited resolution might otherwise prevent initial phasing.

Jonathan AgbenyegaBusiness Development Manager, IUCr

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