LABORATORY OF BIOINFORMATICS AND BIOSTATISTICS

About laboratory

Laboratory of Bioinformatics and Biostatistics is dedicated to:

  • clinical bioinformatics based on NGS sequencing (MiSeq, HiSeq, NextSeq)
  • statistical analysis of biomedical data
  • machine learning methods to analyse omics data (genomics, epigenetics, transcriptomics, proteomics, metabolomics)
  • undergraduate and postgraduate education in biomedical statistics

In the field of clinical bioinformatics, the laboratory, in cooperation with the Clinic of

Gynecology and Obstetrics and the Institute of Molecular Biology and Genomics, participated

in implementation of non-invasive prenatal screening (NIPS) at JFMED CU, and improvements of bioinformatics of NIPS.

In close cooperation with the Institute of Molecular Biology and Genomics JFMED CU, the laboratory takes part in oncological research projects involving NGS sequencing (DNAseq, RNAseq).

Under the supervision of the Institute of Pathological Anatomy of JFMED CU, the laboratory

participates in introducing the TSO 500 panel for genomic profiling of oncological samples. Biostatistical analyses are also used in research projects of other laboratories of BioMed, institutes of JFMED CU, and the clinics of Martin University Hospital. In addition to basic and advanced statistical methods, data analysis process also uses, if appropriate, machine

learning (ML) algorithms. Machine learning is also used for prioritization of biomarkers in omics studies.

Staff

Video tour

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Infrastructure of the laboratory

The laboratory is equipped with an iCompute server and DELL servers. The laboratory caries out bioinformatic analyses using an in-house statistical pipeline which were developed with the assistance of the BioConductor libraries and R, as well as other bioinformatic tools. In cooperation with the Institute of Molecular Biology and Genomics, the laboratory also applies the Qiagen CLC Workbench for NGS analyses. The R software tool is used for biostatistical analyses and machine learning.

Virtual tour

Take a virtual tour of our modern Laboratory of Bioinformatics and Biostatistics.

Projects

ITMS 313011V446, „Integrative strategy for development of personalized medicine of selected oncological diseases and its impact on quality of patient´s life.“

 

ITMS NFP313010AFG5, „Systematic public research infrastructure – biobank for oncological and rare diseases. “

ITMS 313011AUA4, „New methods of laboratory diagnostics and massive screening of

SARS-Cov-2, and identifying the mechanisms of virus behavior in the human body”

 

ITMS 313011AFG4, „Digital biobank. “

APVV-16-0066, „Genomic profiling and transcriptional signature of colorectal cancer. “ (project manager: Assoc.prof. Lasabova, Institute of Molecular Biology and Genomics, JFMED CU).

 

APVV-17-0037, „Development of new in vitro models for amyotrophic lateral sclerosis and testing the safety of neural precursors derived from human induced pluripotent stem cells. “ (project manager Dr. J. Strnádel, Laboratory of Flow Cytometry, Cell Phenotyping and Tissue Engineering, BioMed JFMED CU.

 

APVV-19-0222, „Determination of mitochondrial fitness in diagnostics and prediction of Parkinson´s disease. “ (PI, M. Kolisek, Laboratory of Proteomics and Mitochondriopathies, BioMed JFMED CU).

 

Ministry of Health SR 2018/11-UKMT-7, „Biogenic iron oxides as biomarkers of neurodegenerative diseases mapped by advanced methods of magnetic resonance. “ (PI, Dr. O. Štrbák, Metabolomics Laboratory, BioMed JFMED CU).

 

COST CA17118, „Identifying Biomarkers Through Translational Research for Prevention and Stratification of Colorectal Cancer. “ ( , Z. Lasabova, Institute of Molecular Biology and Genomics).

The most important publications:

Grendár, M., Loderer, D., Lasabová, Z., & Danko, J. (2017). A comment on “Comparing methods for fetal fraction determination and quality control of NIPT samples.” Prenatal Diagnosis 37:12, 1265. https://doi.org/10.1002/pd.5151

Grendár, M., Loderer, D., Lasabová, Z., & Danko, J. (2018). A comment on “Predicting fetoplacental chromosomal mosaicism during non-invasive prenatal testing.” Prenatal Diagnosis 38:9, 720-721. https://doi.org/10.1002/pd.5277

Grendár, M., Loderer, D., Laučeková, Z., Švecová, I., Hrtánková, M., Hornáková, A., Nagy, B., Žúbor, P., Lasabová, Z., & Danko, J. (2019). Uncertainty of fetal fraction determination in Non-Invasive Prenatal Screening by highly polymorphic SNPs. Journal of Biotechnology 229, 32-36. https://doi.org/10.1016/j.jbiotec.2019.04.020

Grendár, M., Loderer, D., Švecová, I., Laučeková, Z., Hrtánková, M., Hornáková, A., Nagy, B., Žúbor, P., Lasabová, Z., & Danko, J. (2019). Non-invasive prenatal screening: from counting chromosomes to estimation of the degree of mosaicism. In Advances in Medicine and Biology, L. V. Berhardt (ed.), Vol, 140, pp, 85-126, NSP (NY).

Grendár, M., Loderer, Lasabová, Z., & Danko, J. (2017). Method for determining the qualification of a  sample for fetal aneuploidy determination in Non invasive Prenatal Testing. EP17203198 (patent)

Grendár, M., Loderer, Lasabová, Z., & Danko, J. (2019). Method for determining the uncertainty of the degree of placental mosaicism of a sample in Non-Invasive Prenatal Screening. EP19158236 (patent)

Mikolka, P., Curstedt, T., Feinstein, R., Larsson, A., Grendar, M., Rising, A. and Johansson, J. (2021). Impact of synthetic surfactant CHF5633 with SP‐B and SP‐C analogues on lung function and inflammation in rabbit model of acute respiratory distress syndrome. Physiological Reports 9:1, p.e14700. https://doi.org/10.14814/phy2.14700

Hanko, M., Grendár, M., Snopko, P., Opšenák, R., Šutovský, J., Benčo, M., Soršák, J., Zeleňák, K. and Kolarovszki, B. (2021). Random Forest–Based Prediction of Outcome and Mortality in Patients with Traumatic Brain Injury Undergoing Primary Decompressive Craniectomy. World neurosurgery. https://doi.org/10.1016/j.wneu.2021.01.002

Malík, M., Dzian, A., Skaličanová, M., Hamada, Ľ., Zeleňák, K. and Grendár, M. (2020). Chest ultrasound can reduce the use of X-ray in postoperative care after thoracic surgery. The Annals of Thoracic Surgery. https://doi.org/10.1016/j.athoracsur.2020.10.019

Lasabová, Z., Kalman, M., Holubeková, V., Grendár, M., Kašubová, I., Jašek, K., Meršaková, S., Malicherová, B., Baranenko, D., Adamek, M., Kruzliak, P., & Plank, L. (2019). Mutation analysis of POLE gene in patients with early-onset colorectal cancer revealed a rare silent variant within the endonuclease domain with potential effect on splicing. Clinical and Experimental Medicine. https://doi.org/10.1007/s10238-019-00558-7

Mestanik, M., Mestanikova, A., Langer, P., Grendar, M., Jurko, A., Sekaninova, N., Visnovcova, N., & Tonhajzerova, I. (2019). Respiratory sinus arrhythmia – testing the method of choice for evaluation of cardiovagal regulation. Respiratory Physiology and Neurobiology. https://doi.org/10.1016/j.resp.2018.08.002

Strnadel, J., Woo, S., Choi, S., Wang, H., Grendar, M., & Fujimura, K. (2018). 3D Culture Protocol for Testing Gene Knockdown Efficiency and Cell Line Derivation. BIO-PROTOCOL. https://doi.org/10.21769/bioprotoc.2874

Cibulka, M., Brodnanova, M., Grendar, M., Grofik, M., Kurca, E., Pilchova, I., Osina, O., Tatarkova, Z., Dobrota, D., & Kolisek, M. (2019). SNPs rs11240569, rs708727, and rs823156 in SLC41A1 Do Not Discriminate Between Slovak Patients with Idiopathic Parkinson’s Disease and Healthy Controls: Statistics and Machine-Learning Evidence. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms20194688

Trafimow, D., Amrhein, V., Areshenkoff, C. N., Barrera-Causil, C. J., Beh, E. J., Bilgiç, Y. K., Bono, R., Bradley, M. T., Briggs, W. M., Cepeda-Freyre, H. A., Chaigneau, S. E., Ciocca, D. R., Correa, J. C., Cousineau, D., de Boer, M. R., Dhar, S. S., Dolgov, I., Gómez-Benito, J., Grendar, M., … Marmolejo-Ramos, F. (2018). Manipulating the alpha level cannot cure significance testing. Frontiers in Psychology.