Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Spiller, C. M.

  • Google
  • 1
  • 4
  • 66

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2009Identification of Suitable Normalizing Genes for Quantitative Real-Time RT-PCR Analysis of Gene Expression in Fetal Mouse Gonads66citations

Places of action

Chart of shared publication
Svingen, Terje
1 / 2 shared
Kashimada, K.
1 / 1 shared
Harley, V. R.
1 / 1 shared
Koopman, P.
1 / 1 shared
Chart of publication period
2009

Co-Authors (by relevance)

  • Svingen, Terje
  • Kashimada, K.
  • Harley, V. R.
  • Koopman, P.
OrganizationsLocationPeople

article

Identification of Suitable Normalizing Genes for Quantitative Real-Time RT-PCR Analysis of Gene Expression in Fetal Mouse Gonads

  • Svingen, Terje
  • Kashimada, K.
  • Harley, V. R.
  • Koopman, P.
  • Spiller, C. M.
Abstract

In biological research, quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) assays are commonly employed to study mRNA abundance in cells and tissues. This type of assay usually relies on assessing transcript abundance relative to constitutively expressed endogenous reference genes. Therefore, it is important that the reference genes themselves are stably expressed in the cells or tissues analyzed, independent of factors such as age, sex, disease or experimental manipulations. Since no gene is expressed at the same level in all cells at all times, suitable reference genes must be identified for the specific cellular system or tissue being investigated. Here, we sought to identify stably expressed endogenous reference genes during embryonic gonad development in the mouse. We measured the transcript abundance of 10 frequently employed normalizing genes, of which 4 were stably expressed in fetal gonads from 11.5 to 14.5 dpc irrespective of sex. Based on our analysis, we suggest that Rn18s, Rps29, Tbp and Sdha are suitable reference genes for qRT-PCR expression studies during early gonad differentiation in the mouse. Copyright (C) 2009 S. Karger AG, Basel

Topics
  • impedance spectroscopy
  • normalizing