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Protein Structure Prediction

Overview of attention for book
Cover of 'Protein Structure Prediction'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Protein Structure Modeling with MODELLER
  3. Altmetric Badge
    Chapter 2 Protein Structure Prediction
  4. Altmetric Badge
    Chapter 3 The MULTICOM Protein Tertiary Structure Prediction System
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    Chapter 4 Modeling of Protein Side-Chain Conformations with RASP
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    Chapter 5 Direct Coupling Analysis for Protein Contact Prediction
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    Chapter 6 ITScorePro: An Efficient Scoring Program for Evaluating the Energy Scores of Protein Structures for Structure Prediction
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    Chapter 7 Assessing the Quality of Modelled 3D Protein Structures Using the ModFOLD Server
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    Chapter 8 3D-SURFER 2.0: Web Platform for Real-Time Search and Characterization of Protein Surfaces.
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    Chapter 9 SPOT-Seq-RNA: Predicting Protein–RNA Complex Structure and RNA-Binding Function by Fold Recognition and Binding Affinity Prediction
  11. Altmetric Badge
    Chapter 10 Protein Structure Prediction
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    Chapter 11 Prediction of Intrinsic Disorder in Proteins Using MFDp2
  13. Altmetric Badge
    Chapter 12 Modeling Protein–Protein Complexes Using the HADDOCK Webserver “Modeling Protein Complexes with HADDOCK”
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    Chapter 13 Predicting the Structure of Protein–Protein Complexes Using the SwarmDock Web Server
  15. Altmetric Badge
    Chapter 14 DOCK/PIERR: Web Server for Structure Prediction of Protein–Protein Complexes
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    Chapter 15 Pairwise and Multimeric Protein-Protein Docking Using the LZerD Program Suite.
  17. Altmetric Badge
    Chapter 16 Protocols for Efficient Simulations of Long-Time Protein Dynamics Using Coarse-Grained CABS Model
Attention for Chapter 8: 3D-SURFER 2.0: Web Platform for Real-Time Search and Characterization of Protein Surfaces.
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

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2 tweeters

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Chapter title
3D-SURFER 2.0: Web Platform for Real-Time Search and Characterization of Protein Surfaces.
Chapter number 8
Book title
Protein Structure Prediction
Published in
Methods in molecular biology, March 2014
DOI 10.1007/978-1-4939-0366-5_8
Pubmed ID
Book ISBNs
978-1-4939-0365-8, 978-1-4939-0366-5
Authors

Xiong Y, Esquivel-Rodriguez J, Sael L, Kihara D, Yi Xiong, Juan Esquivel-Rodriguez, Lee Sael, Daisuke Kihara

Abstract

The increasing number of uncharacterized protein structures necessitates the development of computational approaches for function annotation using the protein tertiary structures. Protein structure database search is the basis of any structure-based functional elucidation of proteins. 3D-SURFER is a web platform for real-time protein surface comparison of a given protein structure against the entire PDB using 3D Zernike descriptors. It can smoothly navigate the protein structure space in real-time from one query structure to another. A major new feature of Release 2.0 is the ability to compare the protein surface of a single chain, a single domain, or a single complex against databases of protein chains, domains, complexes, or a combination of all three in the latest PDB. Additionally, two types of protein structures can now be compared: all-atom-surface and backbone-atom-surface. The server can also accept a batch job for a large number of database searches. Pockets in protein surfaces can be identified by VisGrid and LIGSITE (csc) . The server is available at http://kiharalab.org/3d-surfer/.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 17%
Korea, Republic of 1 17%
Unknown 4 67%

Demographic breakdown

Readers by professional status Count As %
Professor 2 33%
Student > Ph. D. Student 2 33%
Researcher 1 17%
Professor > Associate Professor 1 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 50%
Computer Science 1 17%
Chemistry 1 17%
Engineering 1 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 April 2014.
All research outputs
#2,550,271
of 6,230,817 outputs
Outputs from Methods in molecular biology
#973
of 4,615 outputs
Outputs of similar age
#55,706
of 133,290 outputs
Outputs of similar age from Methods in molecular biology
#16
of 124 outputs
Altmetric has tracked 6,230,817 research outputs across all sources so far. This one has received more attention than most of these and is in the 56th percentile.
So far Altmetric has tracked 4,615 research outputs from this source. They receive a mean Attention Score of 1.5. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 133,290 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 124 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.