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igunduz/README.md

PhD candidate in computational biology at Saarland University, in the Integrative Cellular Biology and Bioinformatics group. I work on how cells establish and change their identity, using single-cell and bulk multi-omics data, including chromatin accessibility, DNA methylation, and transcriptomics, and machine learning that remains interpretable enough to argue with.

Most of what I build ends up as software other people run: three R packages, one Python package, and the reproducible workflows around them. I care about the part after the analysis works, when someone else has to use it without me sitting next to them.

Currently, I am finishing my thesis, developing ARTEMIS, and looking for what comes next.

I'm the developer/maintainer of the following software:

💻 Software Contributions

Package Version Role BioC-release Info
deconvR Developer/Maintainer Simulation and Deconvolution of Omic Profiles
methylTFR Developer/Maintainer Quantification of DNA Methylation Patterns in TFBS
methylTFRAnnotationHg38 Developer/Maintainer AnnotationHub data package for methylTFR on hg38
methylTFRAnnotationMm10 Developer/Maintainer AnnotationHub data package for methylTFR on mm10
ChrAccR Contributor/Co-developer R package for comprehensive analysis of bulk and single-cell chromatin accessibility data
ARTEMIS Developer/Maintainer Python package for Attention-based Regulatory Transcription Factor Explanation from Methylation Interaction Signatures

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  1. BIMSBbioinfo/deconvR BIMSBbioinfo/deconvR Public

    The deconvR is an R package designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model.

    R 10 3

  2. LLMRS LLMRS Public

    LLMRS: Unlocking Potentials of LLM-Based Recommender Systems

    Jupyter Notebook 1

  3. EpigenomeInformatics/methylTFR EpigenomeInformatics/methylTFR Public

    Quantification of DNA Methylation Signatures in Transcription Factor Binding Sites

    R 3

  4. EpigenomeInformatics/ChrAccR EpigenomeInformatics/ChrAccR Public

    Analyzing chromatin accessibility data in R

    R 1