Computational Neuropathology & Oncology (CNO) Research Group

Politecnico di Milano
Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB)


We offer thesis projects for M.Sc. students at Politecnico di Milano!


The group has officially moved from Berlin to the Department of Electronics, Information and Bioingeneering at Politecnico di Milano.


Our R package decompTumor2Sig has just been released with Bioconductor 3.9!


New research article to be presented at the Pacific Symposium of Biocomputing 2020 in Hawaii, USA: "Impact of mutational signatures on microRNA and their response elements"


New research article to be presented at the 19th IEEE International Conference on Bioinformatics and Bioengineering (BIBE) 2019 in Athens, Greece: "Deleterious impact of mutational processes on transcription factor binding sites in human cancer"


New research article: "decompTumor2Sig: identification of mutational signatures active in individual tumors"


New review article/book chapter: "Network-based methods and other approaches for predicting lncRNA functions and disease associations"


The CRC Press book Computational Exome and Genome Analysis is finally being printed!


Our talk submitted to the NETTAB 2017 workshop has been accepted!


Inivited talk at the IEEE conference Confluence-2017, Noida, India.


CNO research group established at Freie Universität Berlin and Charité-Universitätsmedizin Berlin, Germany.

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Basic medical research frequently involves massive data production, such as the determination of genomic sequences and genome-wide gene expression levels by high throughput sequencing. Consequently, the importance of computational biology for medical research has constantly increased over the last decades. Both the analysis of medical data and the development of novel computational methods for this purpose are essential to keep pace with fast evolving experimental techniques and their application to growing numbers of patient samples.

Our Computational Neuropathology & Oncology (CNO) research group (established in March 2015 at Freie Universität Berlin and moved in February 2020 to Polictecnico di Milano) develops novel computational approaches and applies existing methods with a primary focus on computational neuropathology, including cancer genetics/genomics and regulatory changes in metabolic and signaling networks of brain tumors, as well as topics related to the identification and the prioritization of candidate genes for human hereditary disorders of the central nervous system. Our research interest further extends from brain cancer to computational oncology in general, including other solid tumors and leukemias.

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Principal Investigator:

Rosario M. Piro, PhD
Associate Professor of Bioinformatics

E-mail: rosariomichael.piro -AT-

PhD Students:

Verônica Rodrigues de Melo Costa
PhD student
(in collaboration with Freie Universität Berlin and the Long non-coding RNA research group at MPI for Molecular Genetics, Berlin)

Homepage: Verônica@MPIMG


Alumni - Politecnico di Milano:

Alumni - Freie Universität Berlin:

Tobias Balzer
B.Sc. student (2019)

Thesis: Normalisation of mutational signatures for the application on specific genomic sites

Calvinna Caswara
B.Sc. student (2016/2017)

Thesis: Evaluating voting-based consensus clustering of tumor samples using expression patterns from individual metabolic pathways

Willie Ekaputra
B.Sc. student (2019)

Thesis: Analysis of the differential co-expression of protein complexes in breast cancer

Sharen Nicole Heinig
B.Sc. student (2017/2018)

Thesis: Mutability of oncogenes and tumor suppressor genes by different mutational processes

Jan Hoffschulte
B.Sc. student (2017)

Thesis: Evaluierung eines Peak Calling basierten Ansatzes zur Identifizierung intronischer Transkription in RNA-Seq Datensätzen

Marc Horlacher
B.Sc. student (2016/2017)

Thesis: Analyse viraler Proteine im Kontext des humanen Protein-Interaktions-Netzwerks

Jacqueline Krohn
B.Sc. student (2018)

Thesis: Evaluierung der Krankheitsvorhersage mittels 3D-Genexpressionsdaten durch Unterscheidung einzelner Gehirnregionen

Sandra Krüger
B.Sc. student (2017) & M.Sc. student (2019)

Thesis (B.Sc.): Identifizierung von Mutationssignaturen in einzelnen Tumoren
Thesis (M.Sc.): The reimplementation of PathWave and a new approach to combine network topology and gene expression data

Nina Kubiessa
B.Sc. student (2017/2018)

Thesis: Verbesserung von Krankheitsgenvorhersagen basiert auf 3D-Genexpressionsprofilen

Nathaly Reimert
B.Sc. student (2018)

Thesis: Impact of mutational processes on the mutation frequency of tumor suppressors

Bonian Riebe
B.Sc. student (2016)

Thesis: Evaluierung einer Clustering-basierten Pathway-Analyse für mehrere Tumorklassen

Anja Seidel
B.Sc. student (2016)

Thesis: Evaluierung der Haar-Wavelet-Transformation für den Vergleich von 3D-Genexpressionsprofilen zur Vorhersage von krankheitsassoziierten Genen

Arsene Martinien Wabo Ngouambe
M.Sc. student (2018/2019)

Thesis: Identifizierung von rekurrenten somatischen Mutationen in kurzen Introns

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  • PERK-mediated expression of peptidylglycine α-amidating monooxygenase supports angiogenesis in glioblastoma
    Authors: Soni H, Bode J, Nguyen CDL, Puccio L, Neßling M, Piro RM, Bub J, Phillips E, Ahrends R, Eipper BA, Tews B, Goidts V.
    Oncogenesis 9(2):18, 2020. [available at: Nature Publishing]

  • Impact of mutational signatures on microRNA and their response elements
    Authors: Stamoulakatou E, Pinoli P, Ceri S, Piro RM.
    Pac Symp Biocomput 25:250-261, 2020. [available at: World Scientific]


  • Deleterious impact of mutational processes on transcription factor binding sites in human cancer
    Authors: Pinoli P, Stamoulakatou E, Ceri S, Piro RM.
    Proc. of the 19th IEEE International Conference on Bioinformatics and Bioengineering (BIBE) 2019, Athens, Greece, October 28-30, 2019 . [available at: IEEE]

  • decompTumor2Sig: identification of mutational signatures active in individual tumors
    Authors: Krüger S,Piro RM.
    BMC Bioinformatics 20(Suppl 4):152, 2019. [available at: BioMed Central]

  • Network-based methods and other approaches for predicting lncRNA functions and disease associations
    Authors: Piro RM, Marsico A.
    Methods Mol Biol 1912:301-321, 2019. [available at: SpringerLink]


  • The landscape of genomic alterations across childhood cancers
    Authors: Gröbner SN, Worst BC, Weischenfeldt J, Buchhalter I, Kleinheinz K, Rudneva VA, Johann PD, Balasubramanian P, Segura-Wang M, Brabetz S, Bender S, Hutter B, Sturm D, Pfaff E, Hübschmann D, Zipprich G, Heinold M, Eils J, Lawerenz C, Erkek S, Lambo S, Waszak S, Blattmann C, Borkhardt A, Kuhlen M, Eggert A, Fulda S, Gessler M, Wegert J, Kappler R, Baumhoer D, Burdach S, Kirschner-Schwabe R, Kontny U, Kulozik A, Lohmann D, Hettmer S, Eckert C, Bielack S, Nathrath M, Niemeyer C, Richter G, Schulte J, Siebert R, Westermann F, Molenaar JJ, Vassal G, Witt H, ICGC MMML-Seq Project, Burkhardt B, Kratz CP, Witt O, van Tilburg C, Kramm C, Fleischhack G, Dirksen U, Rutkowski S, Frühwald M, von Hoff K, Wolf S, Klingebiel T, Koscielniak E, Landgraf P, Koster J, Resnick AC, Zhang J, Liu Y, Zhou X, Waanders AJ, Zwijnenburg DA, Raman P, Brors B, Weber U, Northcott PA, Pajtler KW, Kool M, Piro RM, Korbel JO, Schlesner M, Eils R, Jones DTW, Lichter P, Chavez L, Zapatka M, Pfister SM.
    Nature 555(7696):321-327, 2018. [available at: Nature Publishing]


  • Computational Exome and Genome Analysis (book)
    Authors: Robinson PN, Piro RM, Jäger M.
    Chapman & Hall/CRC Mathematical and Computational Biology series
    CRC Press (Taylor & Francis Group), Boca Raton, FL, USA, 2017. [available at: CRC Press]

  • Identification of mutational signatures active in individual tumors
    Authors: Krüger S, Piro RM
    Proceedings of the NETTAB 2017 Workshop on Methods, Tools & Platforms for Personalized Medicine in the Big Data Era, held on October 16-18, 2017 in Palermo, Italy.
    PeerJ Preprints 5:e3257v1, 2017. [available at: PeerJ Preprints]

  • Molecular transition of an adult low-grade brain tumor to an atypical teratoid/rhabdoid tumor over a time-course of 14 years
    Authors: Schweizer Y, Meszaros Z, Jones DTW, Koelsche C, Boudalil M, Fiesel P, Schrimpf D, Piro RM, Brehmer S, von Deimling A, Kerl U, Seiz-Rosenhagen M, Capper D.
    Journal of Neuropathology & Experimental Neurology 76(8):655-664, 2017. [available at: Oxford Academic]


  • No correlation between NF1 mutation position and risk of optic pathway glioma in 77 unrelated NF1 patients
    Authors: Hutter S, Piro RM, Waszak SM, Kehrer-Sawatzki H, Friedrich RE, Lassaletta A, Witt O, Korbel JO, Lichter P, Schuhmann MU, Pfister SM, Tabori U, Mautner VF, Jones DTW.
    Human Genetics 135(5):469-475, 2016. [available at: SpringerLink]

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The decompTumor2Sig R package uses quadratic programming to decompose the mutation catalog from an individual tumor sample (or multiple individual tumor samples) into a set of given mutational signatures (either the Alexandrov model or the Shiraishi model), computing weights that reflect the contributions of the signatures to the mutation load of the tumor.

Citing decompTumor2Sig: please cite Krüger S, Piro RM (2017) decompTumor2Sig: identification of mutational signatures active in individual tumors. BMC Bioinformatics 20(Suppl 4):152, 2019. [available at: BioMed Central]


PathWave enables the identification of disease-specific regulation patterns by combining gene expression data and network topology. By analyzing regulatory patterns at multiple scales, PAthWave is capabale to detect both global deregulation of pathways and localized regulatory switches that may still have a singificant impact on metabolic fluxes. PathWave is available here, or from our collaboration partners at Hans Knöll Institute (HKI), Jena:

CITING PATHWAVE: please cite Piro et al. (2014) for PathWave version 2.1, Schramm et al. (2010) for PathWave version 1.0, and both papers (Schramm et al. 2010; Piro et al. 2014) for PathWave in general.

  1. Schramm G, et al. (2010) PathWave: Discovering patterns of differentially regulated enzymes in metabolic pathways. Bioinformatics 26(9):1225-1231.
  2. Piro RM, et al. (2014) Network topology-based detection of differential gene regulation and regulatory switches in cell metabolism and signaling. BMC Systems Biology 8:56.


CGPACE (Candidate Gene Prioritization by Analysis of Co-Expression) is the latest version of the software developed and continusously improved for the following papers:

  1. Piro RM, et al. (2010) Candidate gene prioritization based on spatially mapped gene expression: an application to XLMR. Bioinformatics 26(18):i618-624.
  2. Piro RM, et al. (2011) Evaluation of candidate genes from orphan FEB and GEFS+ loci by analysis of human brain gene expression atlases. PLoS ONE 6(8):e23149.
  3. Piro RM, et al. (2013) Disease-gene discovery by integration of 3D gene expression and transcription factor binding affinities. Bioinformatics 29(4):468-475.

Note: despite its name, CGPACE can be used for data other than gene expression profiles (e.g. total binding affinities/TBAs in paper 3).

Please cite paper 1 when using CGPACE with a Pearson correlation coefficient and paper 3 when using it with the Relative Intensity Overlap (RIO), the use for TBAs and/or a noisy-OR gate for data integration.

See the publications for descriptions of the algorithm, the RIO, the noisy-OR and the use for TBAs; contact me in case of further questions.

CGPACE is released under the terms of the GNU General Public License (Version 2 or later).

Stable releases:
CGPACE-5-2012-12-03.tgz [source code, 57kB]; date: December, 2012.

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For contacting us, please write to:

Prof. Rosario M. Piro

Politecnico di Milano
Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB)
Via Ponzio 34/5
20133 Milano, Italy
Phone: +39 02 2399 3538

E-mail: rosariomichael.piro -AT-
Website: Piro @ DEIB

Impressum/Legal notice according to German legislation

Responsible for the content of this website according to
§ 5 TMG (German Act for Telecommunications Media Services)
and § 55 Abs. 2 RStV (German Interstate Broadcasting Agreement):

Prof. Rosario M. Piro
Politecnico di Milano
Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB)
Via Ponzio 34/5
20133 Milano, Italy
E-mail: rosariomichael.piro -AT-

Liability for the content of linked websites:
This website contains links to external websites on whose content I have no influence and for which I thus cannot take any responsibility. The responsibility for the content of linked websites lies with the providers or administrators of the respective websites. Linked websites have been checked for a possible infringement of laws upon creation of the link. No infringement could be identified when the links were created. A permanent control of the content of the linked websites is not reasonable without a tangible suspicion of the violation of a law. If I should be notified or otherwise become aware of violations of law by the content of a linked website, I will immediately remove the corresponding link.

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