Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues

Sami Kilpinen; Reija Autio; Kalle Ojala; Kristiina Iljin; Elmar Bucher; Henri Sara; Tommi Pisto; Matti Saarela; Rolf Skotheim; Mari Björkman; John-Patrick Mpindi; Saija Haapa-Paananen; Paula Vainio; Henrik Edgren; Maija Wolf; Jaakko Astola; Matthias Nees; Sampsa Hautaniemi; Olli Kallioniemi

doi:10.1186/gb-2008-9-9-r139

Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues

Sami Kilpinen
, Reija Autio
, Kalle Ojala
, Kristiina Iljin
, Elmar Bucher
, Henri Sara
, Tommi Pisto
, Matti Saarela
, Rolf Skotheim
, Mari Björkman
, John-Patrick Mpindi
, Saija Haapa-Paananen
, Paula Vainio
, Henrik Edgren
, Maija Wolf
, Jaakko Astola
, Matthias Nees
, Sampsa Hautaniemi
, Olli Kallioniemi^*

^*Corresponding author for this work

University of Turku
Institute for Molecular Medicine Finland (FIMM)
Tampere University of Technology (TUT)
Rikshospitalet–Radiumhospitalet HF
University of Helsinki

Research output: Contribution to journal › Article › Scientific › peer-review

234 Citations (Scopus)

Abstract

Our knowledge on tissue- and disease-specific functions of human genes is rather limited and highly context-specific. Here, we have developed a method for the comparison of mRNA expression levels of most human genes across 9,783 Affymetrix gene expression array experiments representing 43 normal human tissue types, 68 cancer types, and 64 other diseases. This database of gene expression patterns in normal human tissues and pathological conditions covers 113 million datapoints and is available from the GeneSapiens website.

Original language	English
Journal	Genome Biology
Volume	9
Issue number	R139
DOIs	https://doi.org/10.1186/gb-2008-9-9-r139
Publication status	Published - 2008
MoE publication type	A1 Journal article-refereed

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1186/gb-2008-9-9-r139

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Kilpinen, S., Autio, R., Ojala, K., Iljin, K., Bucher, E., Sara, H., Pisto, T., Saarela, M., Skotheim, R., Björkman, M., Mpindi, J.-P., Haapa-Paananen, S., Vainio, P., Edgren, H., Wolf, M., Astola, J., Nees, M., Hautaniemi, S., & Kallioniemi, O. (2008). Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues. Genome Biology, 9(R139). https://doi.org/10.1186/gb-2008-9-9-r139

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title = "Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues",

abstract = "Our knowledge on tissue- and disease-specific functions of human genes is rather limited and highly context-specific. Here, we have developed a method for the comparison of mRNA expression levels of most human genes across 9,783 Affymetrix gene expression array experiments representing 43 normal human tissue types, 68 cancer types, and 64 other diseases. This database of gene expression patterns in normal human tissues and pathological conditions covers 113 million datapoints and is available from the GeneSapiens website.",

author = "Sami Kilpinen and Reija Autio and Kalle Ojala and Kristiina Iljin and Elmar Bucher and Henri Sara and Tommi Pisto and Matti Saarela and Rolf Skotheim and Mari Bj{\"o}rkman and John-Patrick Mpindi and Saija Haapa-Paananen and Paula Vainio and Henrik Edgren and Maija Wolf and Jaakko Astola and Matthias Nees and Sampsa Hautaniemi and Olli Kallioniemi",

year = "2008",

doi = "10.1186/gb-2008-9-9-r139",

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Kilpinen, S, Autio, R, Ojala, K, Iljin, K, Bucher, E, Sara, H, Pisto, T, Saarela, M, Skotheim, R, Björkman, M, Mpindi, J-P, Haapa-Paananen, S, Vainio, P, Edgren, H, Wolf, M, Astola, J, Nees, M, Hautaniemi, S & Kallioniemi, O 2008, 'Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues', Genome Biology, vol. 9, no. R139. https://doi.org/10.1186/gb-2008-9-9-r139

TY - JOUR

T1 - Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues

AU - Kilpinen, Sami

AU - Autio, Reija

AU - Ojala, Kalle

AU - Iljin, Kristiina

AU - Bucher, Elmar

AU - Sara, Henri

AU - Pisto, Tommi

AU - Saarela, Matti

AU - Skotheim, Rolf

AU - Björkman, Mari

AU - Mpindi, John-Patrick

AU - Haapa-Paananen, Saija

AU - Vainio, Paula

AU - Edgren, Henrik

AU - Wolf, Maija

AU - Astola, Jaakko

AU - Nees, Matthias

AU - Hautaniemi, Sampsa

AU - Kallioniemi, Olli

PY - 2008

Y1 - 2008

N2 - Our knowledge on tissue- and disease-specific functions of human genes is rather limited and highly context-specific. Here, we have developed a method for the comparison of mRNA expression levels of most human genes across 9,783 Affymetrix gene expression array experiments representing 43 normal human tissue types, 68 cancer types, and 64 other diseases. This database of gene expression patterns in normal human tissues and pathological conditions covers 113 million datapoints and is available from the GeneSapiens website.

AB - Our knowledge on tissue- and disease-specific functions of human genes is rather limited and highly context-specific. Here, we have developed a method for the comparison of mRNA expression levels of most human genes across 9,783 Affymetrix gene expression array experiments representing 43 normal human tissue types, 68 cancer types, and 64 other diseases. This database of gene expression patterns in normal human tissues and pathological conditions covers 113 million datapoints and is available from the GeneSapiens website.

U2 - 10.1186/gb-2008-9-9-r139

DO - 10.1186/gb-2008-9-9-r139

M3 - Article

SN - 1474-7596

VL - 9

JO - Genome Biology

JF - Genome Biology

IS - R139

ER -

Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues

Abstract

UN SDGs

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