Publications

Books and Book chapters

  1. Akalin A. “Computational Genomics with R”. Chapman and Hall/CRC, 2020.

  2. Uyar B. “RNA-seq Analysis”. In Akalin A. Computational Genomics with R. Chapman and Hall/CRC, 2020.

  3. Franke V. “ChIP-seq Analysis”. In Akalin A. Computational Genomics with R. Chapman and Hall/CRC, 2020.

  4. Ronen J.“Multi-omics Analysis”. In Akalin A. Computational Genomics with R. Chapman and Hall/CRC, 2020.

  5. Strozzi F., Janssen R., Wurmus R., Crusoe M. R., Githinji G., Di Tommaso P., Belhachemi D., Möller S., Smant G., de Ligt J., Prins P. “Scalable Workflows and Reproducible Data Analysis for Genomics”. In: Anisimova M. (eds) Evolutionary Genomics. Methods in Molecular Biology, vol 1910. Humana, New York Evolutionary Genomics. 2019.

  6. Baubec T & Akalin A. “Genome-Wide Analysis of DNA Methylation Patterns by High-Throughput Sequencing”.In: Aransay A., Lavín Trueba J. (eds) Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing. Springer, 2016.

Selected Peer-reviewed publications

(See all publications at PubMed.)

  1. Dohmen J, Baranovskii A, Ronen J, Uyar B, Franke V, Akalin A. Identifying tumor cells at the single-cell level using machine learning. Genome Biol. 2022 May 30;23(1):123. doi: 10.1186/s13059-022-02683-1. PMID: 35637521; PMCID: PMC9150321.

  2. Kopp W, Monti R, Tamburrini A, Ohler U, Akalin A. Deep learning for genomics using Janggu. Nat Commun. 2020 Jul 13;11(1):3488. doi: 10.1038/s41467-020-17155-y. PMID: 32661261; PMCID: PMC7359359.

  3. Ronen J, Hayat S, Akalin A. Evaluation of colorectal cancer subtypes and cell lines using deep learning. Life Sci Alliance. 2019 Dec 2;2(6):e201900517. doi: 10.26508/lsa.201900517. PMID: 31792061; PMCID: PMC6892438.

  4. Wyler E, Franke V, Menegatti J, Kocks C, Boltengagen A, Praktiknjo S, Walch- Rückheim B, Bosse J, Rajewsky N, Grässer F, Akalin A, Landthaler M. Single-cell RNA-sequencing of herpes simplex virus 1-infected cells connects NRF2 activation to an antiviral program. Nat Commun. 2019 Oct 25;10(1):4878. doi: 10.1038/s41467-019-12894-z. PMID: 31653857; PMCID: PMC6814756.

  5. Wurmus R, Uyar B, Osberg B, Franke V, Gosdschan A, Wreczycka K, Ronen J, Akalin A. PiGx: Reproducible genomics analysis pipelines with GNU Guix. Gigascience. 2018 Oct 2. doi: 10.1093/gigascience/giy123. PubMed PMID: 30277498.

  6. Ronen J, Akalin A. netSmooth: Network-smoothing based imputation for single cell RNA-seq. Version 2. F1000Res. 2018 Jan 3 [revised 2018 Jan 1];7:8. doi: 10.12688/f1000research.13511.2. eCollection 2018.

  7. Wreczycka K, Gosdschan A, Yusuf D, Grüning B, Assenov Y, Akalin A. Strategies for analyzing bisulfite sequencing data.. J Biotechnol., 2017

  8. Uyar B, Yusuf D, Wurmus R,Rajewsky N, Ohler U, Akalin A. RCAS: an RNA centric annotation system for transcriptome-wide regions of interest.. Nucleic Acids Res., 2017

  9. Rampal R *, Akalin A *, Madzo J *, Vasanthakumar A *, Pronier E, Patel J, Li Y, Ahn, et al. DNA Hydroxymethylation Profiling Reveals that WT1 Mutations Result in Loss of TET2 Function in Acute Myeloid Leukemia. Cell Reports, 2014 ( * Equal contribution)

  10. Akalin A * # , Franke V *, Vlahoviček K, Mason CE, Schübeler D. genomation: a toolkit to summarize, annotate and visualize genomic intervals. Bioinformatics , 2014 (# Co-corresponding author, * Equal contribution)

  11. Akalin A#, Kormaksson M, Li S, Garrett-Bakelman FE, Figueroa ME, Melnick A, Mason CE. methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biology, 2012 Oct 3;13(10):R87 #(Co-corresponding author)

  12. Akalin A*, Garrett-Bakelman FE*, Kormaksson M, Busuttil J, et al. Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia. PLoS Genetics 2012;8(6):e1002781. * (Equal Contribution)

Selected Pre-prints

See full list of pre-prints at bioRxiv.

  1. Reproducible genomics analysis pipelines with GNU Guix. Ricardo Wurmus, Bora Uyar, Brendan Osberg, Vedran Franke, Alexander Gosdschan, Katarzyna Wreczycka, Jonathan Ronen, Altuna Akalin bioRxiv 298653; doi: https://doi.org/10.1101/298653

  2. netSmooth: Network-smoothing based imputation for single cell RNA-seq. Jonathan Ronen, Altuna Akalin bioRxiv 234021; doi: https://doi.org/10.1101/234021

  3. Strategies for analyzing bisulfite sequencing data. Katarzyna Wreczycka, Alexander Gosdschan, Dilmurat Yusuf, Bjoern Gruening, Yassen Assenov, Altuna Akalin. bioRxiv 109512; doi: https://doi.org/10.1101/109512

  4. HOT or not: Examining the basis of high-occupancy target regions. Katarzyna Wreczycka, Vedran Franke, Bora Uyar, Ricardo Wurmus, Altuna Akalin. bioRxiv 107680; doi: https://doi.org/10.1101/107680

  5. Mutations In Disordered Regions Cause Disease By Creating Endocytosis Motifs. Katrina Meyer, Bora Uyar, Marieluise Kirchner, Jingyuan Cheng, Altuna Akalin, Matthias Selbach. bioRxiv 141622; doi: https://doi.org/10.1101/141622

  6. FACT sets a barrier for cell fate reprogramming in C. elegans and Human. Ena Kolundzic, Andreas Ofenbauer, Bora Uyar, Anne Sommermeier, Stefanie Seelk, Mei He, Guelkiz Baytek, Altuna Akalin, Sebastian Diecke, Scott Allen Lacadie, Baris Tursun. bioRxiv 185116; doi: https://doi.org/10.1101/185116

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