Validation of genetic variants from NGS data using deep convolutional neural networks

M Vaisband; M Schubert; Franz Josef Gassner; Roland Geisberger; Richard Greil; Nadja Zaborsky; J Hasenauer

doi:10.1186/s12859-023-05255-7

Validation of genetic variants from NGS data using deep convolutional neural networks

M Vaisband, M Schubert, Franz Josef Gassner (Co-author), Roland Geisberger (Co-author), Richard Greil (Co-author), Nadja Zaborsky (Co-author), J Hasenauer

Department of Internal Medicine III - Division of Hematology, Medical Oncology, Hemostaseology, Rheumatology, Infectiology and Oncologic Center

Research output: Contribution to journal › Original Article (Journal) › peer-review

Original language	English
Pages (from-to)	158
Journal	BMC BIOINFORMATICS
Volume	24
Issue number	1
DOIs	https://doi.org/10.1186/s12859-023-05255-7
Publication status	Published - 2023

Keywords

SOMATIC POINT MUTATIONS
RARE MUTATIONS
CANCER
GENOME
IDENTIFICATION
SIGNATURES
DISCOVERY

Access to Document

10.1186/s12859-023-05255-7

Cite this

@article{ee2011a64d5547c386af731ecc79ec40,

title = "Validation of genetic variants from NGS data using deep convolutional neural networks",

keywords = "SOMATIC POINT MUTATIONS, RARE MUTATIONS, CANCER, GENOME, IDENTIFICATION, SIGNATURES, DISCOVERY",

author = "M Vaisband and M Schubert and Gassner, {Franz Josef} and Roland Geisberger and Richard Greil and Nadja Zaborsky and J Hasenauer",

note = "Vaisband, Schubert, Gassner, Geisberger, Greil, Zaborsky: Department of Internal Medicine III with Haematology, Medical Oncology, Haemostaseology, Infectiology and Rheumatology, Oncologic Center; Salzburg Cancer Research Institute - Laboratory for Immunological and Molecular Cancer Research (SCRI-LIMCR); Cancer Cluster Salzburg, Paracelsus Medical University, Salzburg, Austria",

year = "2023",

doi = "10.1186/s12859-023-05255-7",

language = "English",

volume = "24",

pages = "158",

journal = "BMC BIOINFORMATICS",

issn = "1471-2105",

publisher = " BioMed Central",

number = "1",

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T1 - Validation of genetic variants from NGS data using deep convolutional neural networks

AU - Vaisband, M

AU - Schubert, M

AU - Gassner, Franz Josef

AU - Geisberger, Roland

AU - Greil, Richard

AU - Zaborsky, Nadja

AU - Hasenauer, J

N1 - Vaisband, Schubert, Gassner, Geisberger, Greil, Zaborsky: Department of Internal Medicine III with Haematology, Medical Oncology, Haemostaseology, Infectiology and Rheumatology, Oncologic Center; Salzburg Cancer Research Institute - Laboratory for Immunological and Molecular Cancer Research (SCRI-LIMCR); Cancer Cluster Salzburg, Paracelsus Medical University, Salzburg, Austria

PY - 2023

Y1 - 2023

KW - SOMATIC POINT MUTATIONS

KW - RARE MUTATIONS

KW - CANCER

KW - GENOME

KW - IDENTIFICATION

KW - SIGNATURES

KW - DISCOVERY

U2 - 10.1186/s12859-023-05255-7

DO - 10.1186/s12859-023-05255-7

M3 - Original Article (Journal)

C2 - 37081386

SN - 1471-2105

VL - 24

SP - 158

JO - BMC BIOINFORMATICS

JF - BMC BIOINFORMATICS

IS - 1

ER -