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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MitProNet: A Knowledgebase and Analysis Platform of Proteome, Interactome and Diseases for Mammalian Mitochondria
|
|---|---|
| Published in |
PLOS ONE, October 2014
|
| DOI | 10.1371/journal.pone.0111187 |
| Pubmed ID | |
| Authors |
Jiabin Wang, Jian Yang, Song Mao, Xiaoqiang Chai, Yuling Hu, Xugang Hou, Yiheng Tang, Cheng Bi, Xiao Li |
| Abstract |
Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated biological mechanisms underlying mitochondrial functions and human mitochondrial diseases. MitProNet is freely accessible at http://bio.scu.edu.cn:8085/MitProNet. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 5% |
| Korea, Republic of | 1 | 2% |
| Unknown | 40 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 33% |
| Researcher | 10 | 23% |
| Student > Doctoral Student | 7 | 16% |
| Student > Master | 5 | 12% |
| Professor > Associate Professor | 2 | 5% |
| Other | 1 | 2% |
| Unknown | 4 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 30% |
| Biochemistry, Genetics and Molecular Biology | 12 | 28% |
| Medicine and Dentistry | 4 | 9% |
| Computer Science | 3 | 7% |
| Neuroscience | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 7 | 16% |
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 27 December 2015.
All research outputs
#14,788,263
of 22,768,097 outputs
Outputs from PLOS ONE
#123,518
of 194,212 outputs
Outputs of similar age
#143,800
of 260,282 outputs
Outputs of similar age from PLOS ONE
#2,853
of 5,181 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,212 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 260,282 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5,181 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.