Homepage of Neetika Nath


Ongoing Research Projects

Study of Health in Pomerania Data Analysis Community Medicine, Greifswald

Collaboration partners: Prof. Dr. med. Henry Völzke, Till Ittermann - Institute for Community Medicine, University Medicine Greifswald

Our aim in this project is to predict thyroid dysfunction using machine learning algorithms -- an example from the Study of Health in Pomerania. Project and goals -

  • To develop ML based pipeline to test the predictive power example in SHIP data.
  • To identify biosignatures for thyroid dysfunction.
  • To investigate association of biosignatures with thyroid dysfunction.

Heart Rate Variability and Annotation/Segmentation of the ECG

  • Collaboration partners: Dr. Marcus Vollmer, Philipp Sodmann
  • AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017 (see challenge);

Radiation Project

Collaboration partners: Prof. Dr. Harry Scherthan

Ionizing radiation (IR) such as X-rays is frequently used in medical diagnostics where typically low doses of IR are preferred. While chemotherapy expose patients at a high dose at different fractions of doses. Such exposer of cells could lead to damaging DNA double-strand, if left unrepaired, may compromise cellular functions or survival. Currently, there is still only limited knowledge on the molecular impact of IR exposure on a genome-wide level.

  • To investigate IR induced mutation in genomic DNA.

Sreening for Leiomyosarcoma | DKSM

About 50% of all leiomyosarcoma were treated according to the leiomyoma treatment protocol, because malignancy was not suspected at the time of surgery. We are working on a screening system to reduce the number of inadequate surgery using data from the DKSM (German Clinical Center of Excellence for Genital Sarcomas and Mixed Tumors) and outpatient study center.

Bioinformatics Services

Our aim is to improve and develop bioinformatics framework for the analysis of NGS data of various kinds, such as exome and whole-genome sequences and RNAseq data. For various application such as gene profiling, variant annotation, function analysis. Also we develop framework based on machine learning algorithm to predict the disease outcome. Our focus is to analysis, visualisation and interpretation data.

Using machine learning algorithms to analysis medical data.

Student Projects

  • Maja-Celine Cwikla, Dec. 2017 "Classification of the thyroid dysfunction using Multinomial Probit Bayesian Additive Regression Trees"
  • Leonard Caanitz, April 2017 "Can Supervised Learning Be Used to Classify Cardiac Rhythms?"

Analysing NGS data for different biological question

Collaboration Projects

  • Publications
  • Martina Gast, Bernhard H Rauch, Shinichi Nakagawa, Arash Haghikia, Andrzej Jasina, Jan Haas, Neetika Nath, Lars Jensen, Andrea Stroux, Andreas Böhm, Julian Friebel, Ursula Rauch, Carsten Skurk, Stefan Blankenberg, Tanja Zeller, Kannanganattu V Prasanth, Benjamin Meder, Andreas Kuss, Ulf Landmesser, Wolfgang Poller
    Immune system-mediated atherosclerosis caused by deficiency of long noncoding RNA MALAT1 in ApoE-/- mice. Cardiovascular Research; 2018; Vol 115 DOI:

    Neetika Nath, Jennifer Esche, Jessica Müller, Lars R. Jensen, Matthias Port, Mario Stanke, Lars Kaderali, Harry Scherthan, Andreas W. Kuss
    Exome Sequencing Discloses Ionizing-radiation-induced DNA Variants in the Genome of Human Gingiva Fibroblasts. Health physics; 2018; Vol 115 DOI: 10.1097/HP.0000000000000880

    Nicole Endlich, Tim Lange, Jana Kuhn, Paul Klemm, Ahmed M. Kotb, Florian Siegerist, Frances Kindt, Maja T. Lindenmeyer, Clemens D. Cohen, Andreas W. Kuss, Neetika Nath, Rainer Rettig, Uwe Lendeckel, Uwe Zimmermann, Kerstin Amann, Sylvia Stracke, Karlhans Endlich
    BDNF: mRNA expression in urine cells of patients with chronic kidney disease and its role in kidney function
    Journal of Cellular and Molecular Medicine; 2018

    Marcus Vollmer, Philipp Sodmann, Leonard Caanitz, Neetika Nath, Lars Kaderali
    Can Supervised Learning Be Used to Classify Cardiac Rhythms?
    Computing in Cardiology (CinC), 2017; Vol 44; DOI:10.22489/CinC.2017.347-176

    Matthias Rath, Stefanie Spiegler, Neetika Nath, Konrad Schwefel, Nataliya Di Donato, Johannes Gerber, G Christoph Korenke, Yorck Hellenbroich, Ute Hehr, Stephanie Gross, Ulrich Sure, Barbara Zoll, Eberhard Gilberg, Lars Kaderali, Ute Felbor
    Constitutional de novo and postzygotic mutations in isolated cases of cerebral cavernous malformations
    Molecular Genetics and Genomic Medicine, 2016 5: 21-27; DOI:10.1002/mgg3.256.

    Thomas Wolf, Vladimir Shelest, Neetika Nath, Ekaterina Shelest
    CASSIS and SMIPS: Promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes
    Bioinformatics, 2016, 1138-1143;DOI: 10.1093/bioinformatics/btv713

    Neetika Nath, John B. O. Mitchell, Gustavo Caetano-Anolles
    The Natural History of Biocatalytic Mechanisms
    PLoS Computational Biology; 2014;10(5):e1003642; DOI: 10.1371/journal.pcbi.1003642

    James L McDonagh, Neetika Nath, Luna De Ferrari, Tanja van Mourik, John BO Mitchell
    Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules
    Journal of chemical information and modeling; 2014, 54 (3), pp 844-856;DOI: 10.1021/ci4005805

    Lazaros Mavridis, Neetika Nath, John BO Mitchell
    PFClust: a novel parameter free clustering algorithm
    BMC Bioinformatics; 2013; 14:213;DOI:10.1186/1471-2105-14-213

    Rosanna G Alderson, Luna De Ferrari, Lazaros Mavridis, James L McDonagh, John BO Mitchell, Neetika Nath
    Enzyme Informatics.
    Current topics in medicinal chemistry. 2012;12(17):1911-1923.

    N Nath, JBO Mitchell
    Is EC class predictable from reaction mechanism?
    BMC bioinformatics; 2012; 13:60;DOI:10.1186/1471-2105-13-60

    Other things I like to do

    Teaching Experience


    Detection of Radiation-Induced Alterations in the Transcriptome and Exome of Human Gingiva Fibroblasts

    10 April 2018, Barcelona, Spain Next Generation Sequencing Conference 2018 (NGS 2018)

    Chicken Soup of Indian Women!

    04 November 2014, Business and Professional Women Germany - Club Erfurt e. V., Germany

    Understanding enzyme biocatalytic mechanisms and its evolution: bioinformatics point of view

    02 July 2014, Hans-Knoll-Institute (HKI), Jena, Germany

    Classification of Enzymes via Machine Learning Approaches

    10 November 2011, Department of Crop Sciences, University of Illinois, USA

    Poster Presentation

    Lipoinformatics – machine learning approach to study lipid profiless Nath N, Klose C, Gerl M et al. [version 1; not peer reviewed]. F1000Research 2016, 5:2144 (poster) (doi: 10.7490/f1000research.1112979.1)

    The natural history of biocatalytic mechanisms

    International Conference on Intelligent Systems for Molecular Biology (ISMB) and 12th European Conference on Computational Biology (ECCB) 2013

    Quantitative Global Analysis of Enzyme Reaction Mechanisms

    The Seventh International Workshop on Machine Learning in Systems Biology (MLSB13) in Berlin, Germany 2013

    Uniting Cheminformatics and Chemical Theory to Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

    Advancing Computational Chemistry in Scotland, University of St Andrews, UK 2013

    Global Analysis of Enzyme Reaction Mechanisms

    Sixth International Workshop on Machine Learning in Systems Biology held in Basel, Switzerland 2012

    Classification of Enzymes via Machine Learning Approaches

    UseR! University of Warwick, Coventry, UK 2011