CellNet Identity

Graphic strategies

There are two different functions. The first one is to illustrate a lab work with some valuable graphic content: by graphs, stats, and data, hi-res unique renders and shots, etc., but images from stocks also could be used to show the main line of work. You can see some preview gettyimages on this layout, but also you can see that all of them despite the quality are using some cliches about a lab- and biology work.

A specific image connected with your particular study will always be more valuable for a professional reader, and for a regular less-involved in the topic user, a more common stock photo is enough.



The second function is to create a minimalistic visual identity to use in some internal papers and to mark all lab content, to make it recognizable. Because your primary user is very specific and there is no goal to do a broad popularization of science, basic typography rules, color scheme, and some simple patterns are pretty enough to make a full identity system.

You can see below pattern studies, all based on a typical view on a DNA sequencing data and networks visualization.



All of them are line-based, but one group is close to a gradient-imitation and another one is more strict and linear.  Here is a visualization in layouts:


Logo function

Given the narrow specialization of the lab, the logo here works differently than in the retail and the mass market. The main recognizable element of the lab is its name and a graphic mark here is a secondary detail to support the name. Also, it’s important that iconic images for networks, labs and science topic are generally very obvious (except a situation when a study is connected with a very specific and unique graphic element), so in this case, a logo mark could and should be simple and clear, but not necessarily static.

Here is a simple mark that is based on three points and connections between them, so there are numerous of variations of this mark (and all of them are universal) and a possibility to animate it.

 

Group Members

Some words about the team.
Photos by the gallery function (non-clickable there, without an additional caption):


Rounded avatars with some captions (non-recommended for all 15 people):

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Andreas Beyer

Head of department
+49 221-478-84429
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Oliver Hahn

Guest Researcher
+49 221-478-84022
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Michael Müller

Projektkoordination
ADMIRE Köln
+49 221-478-84024
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Selected Publications

Liu Y, Beyer A, Aebersold R (2016)
On the Dependency of Cellular Protein Levels on mRNA Abundance. Cell, 165(3):535-50.


Johannes Stephan, Oliver Stegle, Andreas Beyer (2015)
A random forest approach to capture genetic effects in the presence of population structure. Nature Communications, doi:10.1038/ncomms8432


Mathieu Clément-Ziza, Francesc X Marsellach, Sandra Codlin, Manos A Papadakis, Susanne Reinhardt, María Rodriguez-López, Stuart Martin, Samuel Marguerat, Alexander Schmidt, Eunhye Lee, Christopher T Workman, Jürg Bahler & Andreas Beyer (2014)
Natural genetic variation impacts expression levels of coding, non-coding, and antisense transcripts in fission yeast. Molec. Syst. Biol. 10:764.


Kuhn M, Hyman AA, Beyer A (2014)
Coiled-Coil Proteins Facilitated the Functional Expansion of the Centrosome. PLoS Comp. Biol., 10(6):e1003657


Sikora-Wohlfeld W, Ackermann M, Christodoulou EG, Singaravelu K, Beyer A. (2013)
Assessing computational methods for transcription factor target gene identication based on ChIP-seq data. PLoS Comp. Biol.,9(11):e1003342


Ackermann M, Sikora-Wohlfeld W, Beyer A. (2013)
Impact of natural genetic variation on gene expression dynamics. PLoS Genetics, 9(6):e1003514


Paola Picotti, Mathieu Clément-Ziza, Henry Lam, David S. Campbell, Alexander Schmidt, Eric W. Deutsch, Hannes Röst, Zhi Sun, Oliver Rinner, Lukas Reiter, Qin Shen, Jacob J. Michaelson, Andreas Frei, Simon Alberti, Ulrike Kusebauch, Bernd Wollscheid, Robert L. Moritz, Andreas Beyer and Ruedi Aebersold (2013)
A complete mass spectrometric map of the yeast proteome applied to quantitative trait analysis Nature, doi:10.1038/nature11835


Elefsinioti A, Saraç ÖS, Hegele A, Plake C, Hubner NC, Poser I, Sarov M, Hyman A, Mann M, Schroeder M, Stelzl U, Beyer A. (2011)
Large-scale de novo prediction of physical protein-protein association. Mol Cell Proteomics. 10(11):M111.010629.


Michaelson JJ, Alberts R, Schughart K, Beyer A. (2010)
Data-driven assessment of eQTL mapping methods.BMC Genomics. 7;11:502.


Michaelson JJ, Loguercio S, Beyer A. (2009)
Detection and interpretation of expression quantitative trait loci (eQTL). Methods 48(3):265-76.


Suthram S, Beyer A, Ideker T. (2008)
eQED: an efficient method for interpreting eQTL associations using protein networks. Molec. Syst. Biol. 4:162.


Beyer A, Bandyopadhyay S, Ideker T. (2007)
Integrating physical and genetic maps: from genomes to interaction networks. Nat. Rev. Genet. 8(9):699-710.


R. Brockman, A.Beyer, J. Heinisch, T. Wilhelm (2007)
Posttranscriptional expression regulation: what determines translation rates? PLoS Comput. Biol. 3(3):e57.


A. Beyer, C. Workman, J. Hollunder, D. Radke, U. Möller, T. Wilhelm, T.G. Ideker (2006)
Integrated assessment and prediction of transcription factor binding. PLoS Comput. Biol. 2(6):e70.


J. Hollunder, A. Beyer, T. Wilhelm (2005)
Identification and characterization of protein subcomplexes in yeast. Proteomics 5(8):2082-9.


A. Beyer, T. Wilhelm (2005)
Dynamic simulation of protein complex formation on a genomic scale. Bioinformatics 21(8):1610-6.


A. Beyer, J. Hollunder, H.P. Nasheuer, T. Wilhelm (2004)
Post-transcriptional expression regulation in the yeast Saccharomyces cerevisiae on a genomic scale. Mol. Cell. Proteomics 3(11):1083-92.


Find more publications on PubMed or ResearcherID.

Andreas Beyer

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Affiliations

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CV

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  • 2002 PhD (Systems Science) at the University of Osnabrück, Germany
  • 2002 – 2006: Postdoctoral work at the Leibniz Institute for Age Research, Jena (Thomas Wilhelm) and the University of California San Diego (Trey Ideker)
  • 2007 – 2012: Group leader Cellular Networks & Systems Biology at the BIOTEC, TU-Dresden
  • Since 2013: Professor for Systems Biology at the University of Cologne.

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