Publication:

Genetic approaches to retinal research in zebrafish

Date

Date

Date
2017
Journal Article
Published version

Citations

Citation copied

Niklaus, S., & Neuhauss, S. C. F. (2017). Genetic approaches to retinal research in zebrafish. Journal of Neurogenetics, 31(3), 70–87. https://doi.org/10.1080/01677063.2017.1343316

Abstract

Abstract

Abstract

The zebrafish (Danio rerio) possesses a vertebrate-type retina that is extraordinarily conserved in evolution. This well-organized and anatomically easily accessible part of the central nervous system has been widely investigated in zebrafish, promoting general understanding of retinal development, morphology, function and associated diseases. Over the recent years, genome and protein engineering as well as imaging techniques have experienced revolutionary advances and innovations, creating new possibilities and methods to study zebra

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350 since deposited on 2017-09-12
Acq. date: 2025-11-12

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364 since deposited on 2017-09-12
Acq. date: 2025-11-12

Additional indexing

Creators (Authors)

Journal/Series Title

Journal/Series Title

Journal/Series Title

Volume

Volume

Volume
31

Number

Number

Number
3

Page range/Item number

Page range/Item number

Page range/Item number
70

Page end

Page end

Page end
87

Item Type

Item Type

Item Type
Journal Article

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Language

Language

Language
English

Publication date

Publication date

Publication date
2017-09

Date available

Date available

Date available
2017-09-12

Publisher

Publisher

Publisher

ISSN or e-ISSN

ISSN or e-ISSN

ISSN or e-ISSN
0167-7063

OA Status

OA Status

OA Status
Green

PubMed ID

PubMed ID

PubMed ID

Metrics

Downloads

350 since deposited on 2017-09-12
Acq. date: 2025-11-12

Views

364 since deposited on 2017-09-12
Acq. date: 2025-11-12

Citations

Citation copied

Niklaus, S., & Neuhauss, S. C. F. (2017). Genetic approaches to retinal research in zebrafish. Journal of Neurogenetics, 31(3), 70–87. https://doi.org/10.1080/01677063.2017.1343316

Green Open Access
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