| Title |
Interpreting Chromosomal Rearrangements in the Context of 3-Dimentional Genome Organization: A Practical Guide for Medical Genetics
|
|---|---|
| Published in |
Biochemistry, April 2018
|
| DOI | 10.1134/s0006297918040107 |
| Pubmed ID | |
| Authors |
V. S. Fishman, P. A. Salnikov, N. R. Battulin |
| Abstract |
In this exciting era of "next-gen cytogenetics", the use of novel molecular methods such as comparative genome hybridization and whole genome and whole exome sequencing becomes more and more common in clinics. This results in generation of large amounts of high-resolution patient-specific data and challenges the development of new approaches for interpretation of obtained information. Usually, interpretation of chromosomal rearrangements is focused on alterations of linear genome sequence, underestimating the role of spatial chromatin organization. In this article, we describe the main features of 3-dimentional genome organization, emphasizing their role in normal and pathological development. We highlight some tips to help physicians estimating the impact of chromosomal rearrangements on the patient phenotype. A separate section describes available tools that can be used to visualize and analyze human genome architecture. |
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 % |
|---|---|---|
| France | 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 21% |
| Student > Ph. D. Student | 2 | 14% |
| Other | 1 | 7% |
| Professor | 1 | 7% |
| Lecturer | 1 | 7% |
| Other | 2 | 14% |
| Unknown | 4 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 29% |
| Agricultural and Biological Sciences | 2 | 14% |
| Nursing and Health Professions | 1 | 7% |
| Immunology and Microbiology | 1 | 7% |
| Unknown | 6 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 02 June 2021.
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#3,711,927
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Outputs from Biochemistry
#1,176
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Outputs of similar age
#68,980
of 324,262 outputs
Outputs of similar age from Biochemistry
#22
of 165 outputs
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