A review of automatic particle recognition in Cryo-EM images

Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles inclu...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Sheng wu yi xue gong cheng xue za zhi Jg. 27; H. 5; S. 1178
Hauptverfasser: Wu, Xiaorong, Wu, Xiaoming
Format: Journal Article
Sprache:Chinesisch
Veröffentlicht: China 01.10.2010
Schlagworte:
ISSN:1001-5515
Online-Zugang:Weitere Angaben
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles included in performing reconstructions. Manual selection of particles, even assisted by computer, is a bottleneck of single-particle reconstruction. Cryo-EM image has low signal-to-noise ratio and low contrast, which leads to difficulty in particle picking. Various approaches have been developed to address the problem of automatic particle. This paper describes the application of template-based method, edge based method, feature-based method, neural network, DoG-based and simulated annealing approach in particle picking. The characteristics of various approaches are discussed, and the future development is presented.
AbstractList Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles included in performing reconstructions. Manual selection of particles, even assisted by computer, is a bottleneck of single-particle reconstruction. Cryo-EM image has low signal-to-noise ratio and low contrast, which leads to difficulty in particle picking. Various approaches have been developed to address the problem of automatic particle. This paper describes the application of template-based method, edge based method, feature-based method, neural network, DoG-based and simulated annealing approach in particle picking. The characteristics of various approaches are discussed, and the future development is presented.Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingl
Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles included in performing reconstructions. Manual selection of particles, even assisted by computer, is a bottleneck of single-particle reconstruction. Cryo-EM image has low signal-to-noise ratio and low contrast, which leads to difficulty in particle picking. Various approaches have been developed to address the problem of automatic particle. This paper describes the application of template-based method, edge based method, feature-based method, neural network, DoG-based and simulated annealing approach in particle picking. The characteristics of various approaches are discussed, and the future development is presented.
Author Wu, Xiaorong
Wu, Xiaoming
Author_xml – sequence: 1
  givenname: Xiaorong
  surname: Wu
  fullname: Wu, Xiaorong
  email: wxr@mail.gdufs.edu.cn
  organization: School of Computer Science & Engineering, South China University of Technology, Guangzhou 510641, China. wxr@mail.gdufs.edu.cn
– sequence: 2
  givenname: Xiaoming
  surname: Wu
  fullname: Wu, Xiaoming
BackLink https://www.ncbi.nlm.nih.gov/pubmed/21089695$$D View this record in MEDLINE/PubMed
BookMark eNo1jztrwzAYRTWkNGmav1C0dTLoYckSdAkmfUBKl3Y2svQ5CGzJleyW_PsamkxnuIfLvXdoFWKAFdpQQmghBBVrtMvZt4QwRaRU_BatGSVKSy026GmPE_x4-MWxw2ae4mAmb_Fo0oIeltDGU_CTjwH7gOt0jsXhHfvBnCDfo5vO9Bl2F27R1_Phs34tjh8vb_X-WIyUiakorRbOEWZZax1YrpU0rmNdZbgThjpXWgGu4kTyEsquhYpqrYRsKXCqLWFb9PjfO6b4PUOemsFnC31vAsQ5N4oyyrQk5WI-XMy5HcA1Y1qWpnNzPcz-AB5xUv8
ContentType Journal Article
DBID CGR
CUY
CVF
ECM
EIF
NPM
7X8
DatabaseName Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
DatabaseTitle MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
MEDLINE
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: 7X8
  name: MEDLINE - Academic
  url: https://search.proquest.com/medline
  sourceTypes: Aggregation Database
DeliveryMethod no_fulltext_linktorsrc
ExternalDocumentID 21089695
Genre Review
Research Support, Non-U.S. Gov't
English Abstract
Journal Article
GroupedDBID ---
-05
2B.
5XA
5XF
92F
92I
ABJNI
ACGFS
ALMA_UNASSIGNED_HOLDINGS
CCEZO
CGR
CIEJG
CUY
CVF
CW9
ECM
EIF
F5P
NPM
RPM
TCJ
TGQ
U1G
U5O
7X8
ID FETCH-LOGICAL-p125t-4c95dd02c2bcdec3986adf2f7a3d5a1dd4c5ed730634e4fbe7199856b1e319c02
IEDL.DBID 7X8
ISSN 1001-5515
IngestDate Mon Nov 24 10:46:26 EST 2025
Wed Feb 19 01:49:18 EST 2025
IsPeerReviewed false
IsScholarly true
Issue 5
Language Chinese
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-p125t-4c95dd02c2bcdec3986adf2f7a3d5a1dd4c5ed730634e4fbe7199856b1e319c02
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
PMID 21089695
PQID 812129604
PQPubID 23479
ParticipantIDs proquest_miscellaneous_812129604
pubmed_primary_21089695
PublicationCentury 2000
PublicationDate 2010-Oct
PublicationDateYYYYMMDD 2010-10-01
PublicationDate_xml – month: 10
  year: 2010
  text: 2010-Oct
PublicationDecade 2010
PublicationPlace China
PublicationPlace_xml – name: China
PublicationTitle Sheng wu yi xue gong cheng xue za zhi
PublicationTitleAlternate Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
PublicationYear 2010
SSID ssib002806683
ssib031740855
ssib051374463
ssib001104309
ssib023167930
ssj0042137
Score 1.8685552
SecondaryResourceType review_article
Snippet Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional...
SourceID proquest
pubmed
SourceType Aggregation Database
Index Database
StartPage 1178
SubjectTerms Animals
Automatic Data Processing
Cryoelectron Microscopy - instrumentation
Cryoelectron Microscopy - methods
Cryoelectron Microscopy - trends
Humans
Image Processing, Computer-Assisted - methods
Imaging, Three-Dimensional
Macromolecular Substances - ultrastructure
Molecular Conformation
Particle Size
Ribosomes - chemistry
Ribosomes - ultrastructure
Title A review of automatic particle recognition in Cryo-EM images
URI https://www.ncbi.nlm.nih.gov/pubmed/21089695
https://www.proquest.com/docview/812129604
Volume 27
hasFullText
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07T8NADD4BZWDhIV7lpRtYTyT3TCQkVFWtWFp1AKlbdLm7iA4koWmR4NfjS9LHghhYsmWIZfv7HNufEbqnjDEHSE6MhiDnUH6RNA4ZkanQXjA8ktzUxybUeBxNp_Gknc2p2rHKVU6sE7UtjP9H_gBABNAkA_5UfhB_NMo3V9sLGruow4DJ-LhU060mUOgFrbarC8DXDZpSvwQeb9gzIKmX-1q7twiZ4rVYfJPYOW0kOL1qEQGiIX4npTU4DY_--VnH6LBlpbjXuNEJ2vl-O0WPPdwstuAiw3q5KGp1V1y2zobXs0dFjmc57s-_CjIY4dk7pKjqDL0OBy_9Z9IeWyAlcJwF4SYW1gbU0NRYZ1gcSW0zminNrNChtdwIZyEfSMYdz1Kn_HaekGnoIIpNQM_RXl7k7hLhNDNMKSs9G-JKmchxrpXhkqaBylzQRXhliwSc2XcodO6KZZWsrdFFF409k7IR3UigNI1iGYurv1--Rgd1j78eubtBnQwC2d2iffO5mFXzu9pJ4DmejH4Anxi_2A
linkProvider ProQuest
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+review+of+automatic+particle+recognition+in+Cryo-EM+images&rft.jtitle=Sheng+wu+yi+xue+gong+cheng+xue+za+zhi&rft.au=Wu%2C+Xiaorong&rft.au=Wu%2C+Xiaoming&rft.date=2010-10-01&rft.issn=1001-5515&rft.volume=27&rft.issue=5&rft.spage=1178&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1001-5515&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1001-5515&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1001-5515&client=summon