Literature DB >> 17709968

The Genome Austria Tissue Bank (GATiB).

M Asslaber1, P M Abuja, K Stark, J Eder, H Gottweis, M Trauner, H Samonigg, H J Mischinger, W Schippinger, A Berghold, H Denk, K Zatloukal.   

Abstract

In the context of the Austrian Genome Program, a tissue bank is being established (Genome Austria Tissue Bank, GATiB) which is based on a collection of diseased and corresponding normal tissues representing a great variety of diseases at their natural frequency of occurrence from a non-selected Central European population of more than 700,000 patients. Major emphasis is put on annotation of archival tissue with comprehensive clinical data, including follow-up data. A specific IT infrastructure supports sample annotation, tracking of sample usage as well as sample and data storage. Innovative data protection tools were developed which prevent sample donor re-identification, particularly if detailed medical and genetic data are combined. For quality control of old archival tissues, new techniques were established to check RNA quality and antigen stability. Since 2003, GATiB has changed from a population-based tissue bank to a disease-focused biobank comprising major cancers such as colon, breast, liver, as well as metabolic liver diseases and organs affected by the metabolic syndrome. Prospectively collected tissues are associated with blood samples and detailed data on the sample donor's disease, lifestyle and environmental exposure, following standard operating procedures. Major emphasis is also placed on ethical, legal and social issues (ELSI) related to biobanks. A specific research project and an international advisory board ensure the proper embedding of GATiB in society and facilitate international networking. (c) 2007 S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2007        PMID: 17709968     DOI: 10.1159/000104453

Source DB:  PubMed          Journal:  Pathobiology        ISSN: 1015-2008            Impact factor:   4.342


  11 in total

1.  [Biobanking. Sustainable use of biological resources on the example of the Biobank Graz].

Authors:  T Macheiner; B Huppertz; K Sargsyan
Journal:  Pathologe       Date:  2013-07       Impact factor: 1.011

2.  IT Infrastructure Components for Biobanking.

Authors:  H U Prokosch; A Beck; T Ganslandt; M Hummel; M Kiehntopf; U Sax; F Uckert; S Semler
Journal:  Appl Clin Inform       Date:  2010-11-24       Impact factor: 2.342

3.  Establishment of a lung cancer biobank of a southern chinese population.

Authors:  Huiling Li; Yuan Qiu; Xin Zhang; Xin Xu; Dongjiang Liao; Wei Wang; Danping Wen; Qiuhua Dong; Haifeng Xian; Daoyuan Wang; Nanshan Zhong; Jianxing He
Journal:  J Thorac Dis       Date:  2009-12       Impact factor: 2.895

Review 4.  [Preanalytics and biobanking : Influence of preanalytical factors on tissue sample quality].

Authors:  K-F Becker; J Wipperfürth; E Herpel
Journal:  Pathologe       Date:  2018-07       Impact factor: 1.011

5.  Genetic data sharing and privacy.

Authors:  Marco D Sorani; John K Yue; Sourabh Sharma; Geoffrey T Manley; Adam R Ferguson
Journal:  Neuroinformatics       Date:  2015-01

6.  Clusterin associates with altered elastic fibers in human photoaged skin and prevents elastin from ultraviolet-induced aggregation in vitro.

Authors:  Elke Janig; Martin Haslbeck; Ariane Aigelsreiter; Nathalie Braun; Daniela Unterthor; Peter Wolf; Noor M Khaskhely; Johannes Buchner; Helmut Denk; Kurt Zatloukal
Journal:  Am J Pathol       Date:  2007-09-14       Impact factor: 4.307

7.  Developing a tissue resource to characterize the genome of pancreatic cancer.

Authors:  Georgios Voidonikolas; Marie-Claude Gingras; Sally Hodges; Amy L McGuire; Changyi Chen; Richard A Gibbs; F Charles Brunicardi; William E Fisher
Journal:  World J Surg       Date:  2009-04       Impact factor: 3.352

8.  Organocatalytic removal of formaldehyde adducts from RNA and DNA bases.

Authors:  Saswata Karmakar; Emily M Harcourt; David S Hewings; Florian Scherer; Alexander F Lovejoy; David M Kurtz; Thomas Ehrenschwender; Luzi J Barandun; Caroline Roost; Ash A Alizadeh; Eric T Kool
Journal:  Nat Chem       Date:  2015-08-03       Impact factor: 24.427

9.  Genome-wide massively parallel sequencing of formaldehyde fixed-paraffin embedded (FFPE) tumor tissues for copy-number- and mutation-analysis.

Authors:  Michal R Schweiger; Martin Kerick; Bernd Timmermann; Marcus W Albrecht; Tatjana Borodina; Dmitri Parkhomchuk; Kurt Zatloukal; Hans Lehrach
Journal:  PLoS One       Date:  2009-05-14       Impact factor: 3.240

10.  High quality copy number and genotype data from FFPE samples using Molecular Inversion Probe (MIP) microarrays.

Authors:  Yuker Wang; Victoria E H Carlton; George Karlin-Neumann; Ronald Sapolsky; Li Zhang; Martin Moorhead; Zhigang C Wang; Andrea L Richardson; Robert Warren; Axel Walther; Melissa Bondy; Aysegul Sahin; Ralf Krahe; Musaffe Tuna; Patricia A Thompson; Paul T Spellman; Joe W Gray; Gordon B Mills; Malek Faham
Journal:  BMC Med Genomics       Date:  2009-02-19       Impact factor: 3.063

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.