• SpiderSeqR: R package to automate searching​ and collection of high-throughput multi-omic data-sets from NCBI SRA and GEO.

      Sozanska et al., 2020 bioRxiv

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• Pangaea: A modular Natural Language Processing toolkit for high-throughput mining of biomedical literature.

      Pirvan and Samarajiwa, 2020 bioRxiv

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• Remoat: Microarray platform re-annotation resource (website code base)

      Barbosa-Morais et al., 2009 Nuc. Acids Res.

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• Interferome: Data-resource for type I,II and III Interferon (IFN) target gene identification. Samarajiwa et al., 2009, Nuc. Acids Res.

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• Rcade: R/Bioconductor package for TF direct target identification. Collaboration With Dr Jonathan Cairns and Prof. Simon Tavaré.

      Kirschner and Samarajiwa et al., PLoS Genet. 2015

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Under peer review:

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• COBRA-tft: TF direct target identification by integration of ChIP-seq datasets and RNA-seq data

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• ISGverse: A collection of reliable IFN regulated genes identified using RNA-seq data integration and a bespoke statistical method.

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Machine & Deep Learning models:

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• EMethylNET: ML/DL model for cancer detection. Newsham et al., 2024

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      GitHub: https://github.com/ss-lab-cancerunit/EMethylNet_code

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      CodeOcean (platform for hosting an executable and reproducible results capsule):   https://codeocean.com/capsule/1717654/tree

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• MethylBoostER: ML model for renal cancer subtype detection. Rossi et al., Sci Adv 2022 

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      GitHub: https://github.com/ss-lab-cancerunit/MethylBoostER

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      Zenodo (EU open research repository): https://zenodo.org/records/6463893

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• Piranha: ML/DL model for chromatin structure prediction. Martens et al., 2020

 

 

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Coming Soon:

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• FRoGS 

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• InterferonScape 

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• Senesceome-KG

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