Dr. Daniel Ziemek

(formerly Daniel Hanisch)

Head of Algorithms and Platforms
Computational Sciences at Pfizer

35 Cambridgepark Drive
Cambridge, MA, 02140

phone: +1 - 617 - 417 - 5493
eMail: Daniel.Ziemek@pfizer.com or

View Daniel Ziemek's profile on LinkedIn
Dr. Daniel Ziemek

Daniel Ziemek

My main interest is to harness the current wealth of genetic, transcriptional, and metabolomic data to solve biomedical problems. To that end, I am leading a team of talented scientists spanning various disciplines. We design, implement and apply innovative methods to impact R&D ranging from target validation to prediction of toxicological endpoints to biomarker discovery in clinical trials. I am involved in several large-scale academic and industrial collaborations to extend our computational toolkit in this area and served on Ph.D. thesis committees for great students at Boston University and Georgia Tech.

In my opinion, the importance of prior knowledge has been severely undervalued in current research. Reliable ways to interpret new data in light of established findings are still not well developed. This leads to a massive amount of costly, redundant experiments - computationally as well as in the lab. My own research is focused on establishing platforms that give a deep understanding of how well experimental results can be explained by known biology, and what parts point to truly novel hypotheses. Using these platforms, we are supporting projects along the R&D pipeline directly, and have successfully applied causal prior knowledge to generate testable hypotheses for project teams based on transcriptomics, genetics, and metabolomics data.

Brief CV (complete CV as pdf)

I received my diploma (~ M.Sc.) in computer science from the University of Bonn in 2000. From 2000 to 2004, I worked as a research assistant in the bioinformatics group at the Fraunhofer Institute SCAI. I enrolled in the Ph.D. program of the Ludwig-Maximilians-Universität München (LMU) in 2002 and received my Ph.D. in December 2004. My supervisors were Prof. Dr. Ralf Zimmer and Prof. Dr. Thomas Lengauer. My primary research interest was and still is the development of innovative analysis methods for gene or protein expression data leveraging prior knowledge in the form of biological networks (cf. publications).

In February 2004, I joined Sanofi-Aventis to work in the field of pathway informatics and had the good fortune to stay for one year at the Sanofi-Aventis Cambridge Genomics Center in beautiful Boston. I was the Scientific Lead for a project to enable enterprise-wide pathway analysis of experimental data. In that role, I successfully applied innovative algorithms to projects while at the same time collaborating with the software team on the best design patterns and technologies to use for a scalable, enterprise solution. I was also involved with several other projects including ODE-based simulation of cardiac arrythmias and statistical evaluation of high-throughput screening (HTS) results.

In October 2008, I joined the Computational Sciences Center of Emphasis at Pfizer in Cambridge, MA as a Senior Principal Scientist. My main responsibility was the application of statistical / machine learning techniques to computational biology and chemistry projects across Pfizer research. At the same time, I was the Biological Systems Domain Lead for the CS CoE. In the intersection of these two roles, I designed and implemented methods to leverage large-scale curated literature information for the interpretation of transcriptional profiling and genetics variant sequencing data (received Innovation Award in 2010).

In September 2011, I was promoted to Associate Research Fellow and am now leading the Algorithms and Methods Group of the Computational Sciences.

I am always interested in new challenges, interesting suggestions or discussions, so please don't hesitate to contact me by email.



Causal Reasoning on Biological Network: Interpreting Transcriptional Changes.
L Chindelevitch, D Ziemek (co-first author), A Enayetallah, R Randhawa, B Sidders, C Brockel, E Huang.

2012,  Bioinformatics
Silencing of enzymes involved in ceramide biosynthesis causes distinct global alterations of lipid homeostasis and gene expression.
W Ruangsiriluk, SE Grosskurth, D Ziemek, M Kuhn, SG des Etages, OL Francone.

2012,  Journal of Lipid Research 53 (8), 1459-1471
Causal Correlation Set Analysis: Detecting active regulators in disease populations using prior causal knowledge.
CL Huang, J Lamb, L Chindelevitch, J Kostrowicki, J Guinney, C DeLisi, D Ziemek.

2012,  BMC bioinformatics 13 (1), 46
Assessing Statistical Significance in Causal Graphs.
L Chindelevitch, P. Loh, A. Enayetallah, B Berger, D Ziemek.

2012,  BMC Bioinformatics 13 (1), 35


Modeling the Mechanism of Action of a DGAT1 Inhibitor Using a Causal Reasoning Platform.
A Enayetallah, D Ziemek (co-first author), M Leininger, R Randhawa, J Yang, T Manion, D Mather, W Zavadoski, M Kuhn, J Treadway, S des Etages, E Gibbs, N Greene, C Steppan.
2011, PLoS ONE, 6(11):e27009
Causal Reasoning on Biological Network: Interpreting Transcriptional Changes (Extended Abstract).
L Chindelevitch, D Ziemek (co-first author), A Enayetallah, R Randhawa, B Sidders, C Brockel, E Huang.

2011,  Lecture Notes in Computer Science (RECOMB 2011).


Network-driven Analysis Methods and their Application to Drug Discovery.
D Ziemek, C Brockel

2010, Chapter in  Handbook of Research on Computational and Systems Biology: Interdisciplinary Application.


Characterization of human cardiac Kv1.5 inhibition by the novel atrial-selective antiarrhythmic compound AVE1231.
JR Ehrlich H. Ocholla,  D Ziemek, H Rütten, SH Hohnloser, H Gögelein

2008,  J Cardiovasc Pharmacol. 51(4):380-7.


New Analysis Methods For Gene Expression Data via Construction and Incorporation of Biological Networks (Ph.D. Thesis)
Daniel Hanisch
2005, Shaker Verlag (ISBN 3-8322-3803-4)
ProMiner: Rule-based protein and gene entity recognition
Daniel Hanisch, Katrin Fundel, Theo Mevissen, Ralf Zimmer, Juliane Fluck
2005, BMC Bioinformatics 6 Suppl 1:S14


New Methods for Joint Analysis of Biological Networks and Expression Data
Florian Sohler, Daniel Hanisch, Ralf Zimmer
2004, Bioinformatics 20(10): 1517-1521.
ToPNet – an application for interactive analysis of expression data and biological networks
Daniel Hanisch, Florian Sohler, Ralf Zimmer
Bioinformatics 20(9): 1470-1471


New Methods for Joint Analysis of Biological Networks and Expression Data
Florian Sohler, Daniel Hanisch, Ralf Zimmer
2003, Proceedings of the German Conference on Bioinformatics (GCB).
Gene Expression in Chondrocytes Assessed with Use of Microarrays
Thomas Aigner, Alexander Zien, Daniel Hanisch, and Ralf Zimmer
2003, J Bone Joint Surg Am 85: 117-123.
Playing Biology's Name Game: Identifying Protein Names in Scientific Text
Daniel Hanisch, Juliane Fluck, Heinz-Theodor Mevissen, Ralf Zimmer
Proceedings of the Pacific Symposium on Bioinformatics (PSB).


Co-Clustering of Biological Networks and Gene Expression Data
Daniel Hanisch, Alexander Zien, Ralf Zimmer, Thomas Lengauer
Bioinformatics, 18, Suppl. 1 ISMB'02, pages 145S-154S.
ProML - the Protein Markup Language for specification of protein sequences, structures and families
Daniel Hanisch, Ralf Zimmer and Thomas Lengauer
2002, In Silico Biol. 2, 0029. http://www.bioinfo.de/isb/2002/02/0029/
Improving fold recognition of protein threading by experimental distance constraints
Mario Albrecht, Daniel Hanisch, Ralf Zimmer and Thomas Lengauer
2002, In Silico Biol. 2, 0030. http://www.bioinfo.de/isb/2002/02/0030/
A new method for unification of existing protein structure- and sequence-families
Jan Freudenberg, Ralf Zimmer, Daniel Hanisch and Thomas Lengauer
2002, In Silico Biol. 2, 0031, <


A New Method for the Fast Solution of Protein-3D-Struct2res,Combining Experiments and Bioinformatics
Daniel Hoffmann, Volker Schnaible, Stephan Wefing, Mario Albrecht, Daniel Hanisch, and Ralf Zimmer
Proceedings of the 2nd caesarium, Bonn, November 1-3, 2001, Ed.: K.-H. Hoffmann. Berlin: Springer, 2002.