Alumni and theses

PhD theses

Julia Casado:

Proteogenomics methods for translational cancer research (2021)

Alejandra Cervera:

Transcriptomics analysis and its applications in cancer (2020)

Amjad Alkodsi:

Computational investigation of cancer genomes (2019)

Emilia Kozlowska:

Mathematical modeling of treatment resistance in cancer (2019)

Katherine Icay:

Computational analysis of microRNAs in biomedicine (2018)

Chengyu Liu:

Computational integrative analysis of biological networks in cancer (2017)

Ping Chen:

Quantitative study of transcriptome dynamics during evolution and treatment resistance in cancer (2016)

Riku Louhimo:

Biomedical data integration in cancer genomics (2015)

Ville Rantanen:

Integration platform for biomedical image analysis (2015)

Kristian Ovaska:

Computational methods for analyzing complex high-throughput data from cancers (2014)

Sirkku Karinen:

Computational methods to analyze molecular determinants behind phenotypes (2013)

Marko Laakso:

Data integration methods to interpret genome-scale data from cancers (2012)

Anna-Maria Lahesmaa-Korpinen:

Computational approaches in high-throughput proteomics data analysis (2012)

MD theses

Rony Lindell:

Next-generation sequencing using the Anduril framework (2016)

Msc theses

Oskari Lehtonen:

Fully convolutional neural networks for nuclei segmentation and type classification (2021)

Kari Lavikka:

Grammar-based interactive genome visualization (2020)

Mikko Kivikoski:

Computational analysis of tumour evolution: reconstructing evolutionary history of four uterine leiomyomas in one patient (2016)

Julia Casado:

Integrating ENCODE data to model transcriptional regulation (2014)

Chiara Facciotto:

MethylFlow: A novel pipeline for preprocessing and analysis of bisulfite sequencing DNA methylation data (2013)

Erkka Valo:

Prediction of drug effects in gene regulatory networks: Boolean modeling approach (2013)

Amjad Alkodsi:

Comparison of somatic copy number alteration detection algorithms in whole-genome and whole-exome data (2013)

Alejandra Cervera:

Computational framework for systematic and scalable analysis of deep sequencing transcriptomics data (2012)

Ali Oghabian:

Application of the biclustering and conventional clustering methods in microarray data analysis (2011)

Chengyu Liu:

Ensemble learning for predicting breast cancer metastasis using high-throughput expression data (2010)

Kari Nousiainen:

Petri nets in simulating TNF-α induced cellular signaling (2010)

Riku Louhimo:

Integrating exon array comparative genomic hybridization data in glioblastoma (2010)

Kristian Ovaska:

Component-based workflow framework for gene expression microarray analysis (2009)

Ping Chen:

Computational approaches for alternative splicing analysis using exon arrays (2009)

Sirkku Karinen:

Computational identification of compound heterozygotes using haplotypes (2008)

Marko Laakso:

Computational identification of recessive mutations in cancer using high throughput SNP-arrays (2007) [e-thesis]

BSC theses

Yilin Li:

Signatuurit mutaatioprosessien mallina [Signatures as a model of mutational processes] (2020)

Erkka Valo:

Identifying combinatorial intervention strategies for gene regulatory networks (2012)

Janne Peltola:

Androgen receptor induced gene regulation prediction in prostate cancer with random forest algorithm (2008)