| Title |
Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of diabetes mellitus type 2
|
|---|---|
| Published in |
BMC Bioinformatics, December 2014
|
| DOI | 10.1186/1471-2105-15-s17-s5 |
| Pubmed ID | |
| Authors |
Chang Liu, Lili Lu, Quan Kong, Yan Li, Haihua Wu, William Yang, Shandan Xu, Xinyu Yang, Xiaolei Song, Jack Y Yang, Mary Qu Yang, Youping Deng |
| Abstract |
Diabetes mellitus of type 2 (T2D), also known as noninsulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, is a common disease. It is estimated that more than 300 million people worldwide suffer from T2D. In this study, we investigated the T2D, pre-diabetic and healthy human (no diabetes) bloodstream samples using genomic, genealogical, and phonemic information. We identified differentially expressed genes and pathways. The study has provided deeper insights into the development of T2D, and provided useful information for further effective prevention and treatment of the disease. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 4% |
| Unknown | 23 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 21% |
| Student > Master | 5 | 21% |
| Student > Bachelor | 4 | 17% |
| Researcher | 4 | 17% |
| Other | 2 | 8% |
| Other | 4 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 38% |
| Medicine and Dentistry | 4 | 17% |
| Biochemistry, Genetics and Molecular Biology | 3 | 13% |
| Computer Science | 3 | 13% |
| Nursing and Health Professions | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 2 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 07 January 2015.
All research outputs
#15,314,171
of 22,776,824 outputs
Outputs from BMC Bioinformatics
#5,373
of 7,276 outputs
Outputs of similar age
#209,427
of 354,389 outputs
Outputs of similar age from BMC Bioinformatics
#100
of 150 outputs
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