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research:publications [2024/12/06 10:14] – mikael | research:publications [2025/09/02 14:51] (current) – mikael | ||
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==== Pre-prints of note ==== | ==== Pre-prints of note ==== | ||
- | - Tule S, Foley G and Bodén M. Do Protein Language Models Learn Phylogeny? | + | - Chen R et al [[https://doi.org/ |
- | - Shen S et al. An integrated cell barcoding and computational analysis pipeline for scalable analysis | + | - Balderson B et al. Comprehensive molecular impact mapping |
+ | | ||
==== Journal papers ==== | ==== Journal papers ==== | ||
- | - Mora A, Schmidt C, Balderson B, Frezza C and Bodén M. (Accepted) SiRCle (Signature Regulatory Clustering) model integration reveals mechanisms of phenotype regulation in renal cancer. //Genome Medicine// 16: 144. DOI [[https:// | + | |
- | - Joshi P et al. (Accepted). Phage Anti-Pycsar Proteins Efficiently Degrade β-Lactam Antibiotics. //Applied Biosciences// | + | - Sinniah E et al. Epigenetic constraint of cellular genomes evolutionarily links genetic variation to function. Accepted //Nucleic Acids Research//. [[https:// |
- | - Prabhu A, Tule S, Chuvochina M, Bodén M, McIlroy SJ, Zaugg J and Rinke C. (Accepted) Machine learning and metagenomics identifies uncharacterized taxa inferred to drive biogeochemical cycles in a subtropical hypereutrophic estuary. //ISME Communications// | + | - Low YS, Roche SG, Aleksandrova NA, Foley G, Low JKK, Box JK, Croll TI, Chassagnon IR, Lott JS, Deplazes E, Bodén M, Hurst MRH, Piper SJ and Landsberg MJ. Complete structures of the YenTc holotoxin prepore and pore reveal the evolutionary basis for chitinase incorporation into ABC toxins. Accepted //Nature Communications// |
- | - Tule S, Foley G, Zhao C, Forbes M and Bodén M. (Accepted) Optimal Phylogenetic Reconstruction of Insertion and Deletion Events. // | + | - Shen S, Werner T, Lukowski SW, Andersen S, Sun Y, Shim WJ, Mizikovsky D, Kobayashi S, Outhwaite J, Chin HS, Chen X, Chapman G, Martin E, Xia D, Pham D, Su Z, Kim D, Yang P, Tan MC, Sinniah E, Zhao Q, Negi S, Redd MA, Powell JE, Dunwoodie SL, Tam P, Bodén M, Ho JWK, Nguyen Q and Palpant NJ. (2025) Atlas of multilineage stem cell differentiation reveals TMEM88 as a developmental regulator of blood pressure. //Nature Communications// |
- | - Balderson B, Fane M, Harvey TJ, Piper M, Smith A and Bodén M. (2024) Systematic analysis of the Transcriptional Landscape of Melanoma Reveals Drug-target Expression Plasticity. //Briefings in Functional Genomics//. DOI [[https:// | + | - Tule S, Foley G and Bodén M. (2025) Do Protein Language Models Learn Phylogeny? //Briefings in Bioinformatics// |
- | - Teshima M, Sutiono S, Döring M, Beer B, Boden M, Schenk G and Sieber V (2023) Development of a Highly Selective NAD+-Dependent Glyceraldehyde Dehydrogenase and its Application in Minimal Cell-Free Enzyme Cascades. // | + | - Zhao QY, Shim WJ, Sun Y, Sinniah E, Shen S, Bodén M and Palpant N. (2025) TRIAGE: An R Package for Regulatory Gene Analysis. //Briefings in Bioinformatics// |
+ | | ||
+ | - Joshi P et al. (2024) Phage Anti-Pycsar Proteins Efficiently Degrade β-Lactam Antibiotics. //Applied Biosciences// | ||
+ | - Prabhu A, Tule S, Chuvochina M, Bodén M, McIlroy SJ, Zaugg J and Rinke C. (2024) Machine learning and metagenomics identifies uncharacterized taxa inferred to drive biogeochemical cycles in a subtropical hypereutrophic estuary. //ISME Communications// | ||
+ | - Tule S, Foley G, Zhao C, Forbes M and Bodén M. (2024) Optimal Phylogenetic Reconstruction of Insertion and Deletion Events. // | ||
+ | - Balderson B, Fane M, Harvey TJ, Piper M, Smith A and Bodén M. (2024) Systematic analysis of the Transcriptional Landscape of Melanoma Reveals Drug-target Expression Plasticity. //Briefings in Functional Genomics// | ||
+ | - Teshima M, Sutiono S, Döring M, Beer B, Boden M, Schenk G and Sieber V (2023) Development of a Highly Selective NAD+-Dependent Glyceraldehyde Dehydrogenase and its Application in Minimal Cell-Free Enzyme Cascades. // | ||
- Balderson B, Piper M, Thor S and Bodén M. (2023) Cytocipher detects significantly different populations of cells in single cell RNA-seq data. // | - Balderson B, Piper M, Thor S and Bodén M. (2023) Cytocipher detects significantly different populations of cells in single cell RNA-seq data. // | ||
- Sun Y, Shim W, Shen S, Sinniah E, Pham D, Su Z, Mizikovsky D, White MD, Ho JWK, Nguyen Q, Bodén M, Palpant NJ. (2023) Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity. //Nucleic Acids Research//. DOI [[https:// | - Sun Y, Shim W, Shen S, Sinniah E, Pham D, Su Z, Mizikovsky D, White MD, Ho JWK, Nguyen Q, Bodén M, Palpant NJ. (2023) Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity. //Nucleic Acids Research//. DOI [[https:// | ||
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- Hawkins J, Mahony D, Maetschke S, Wakabayashi M, Teasdale RD and Bodén M (2007) Identifying novel peroxisomal proteins. // | - Hawkins J, Mahony D, Maetschke S, Wakabayashi M, Teasdale RD and Bodén M (2007) Identifying novel peroxisomal proteins. // | ||
- Hawkins J, Davis L and Bodén M (2007) // | - Hawkins J, Davis L and Bodén M (2007) // | ||
- | - Bauer, D., Bodén M., Thier, R. and Gillam, E. M. STAR: Predicting recombination sites from amino acid sequence. //BMC Bioinformatics//, | + | - Bauer D, Bodén M, Thier R and Gillam |
- | - Bodén, M. and Bailey, T. L. Identifying sequence regions undergoing conformational change via predicted continuum secondary structure. // | + | - Bodén M and Bailey |
- | - Bodén, M., Yuan, Z. and Bailey, T. L. Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures. //BMC Bioinformatics// | + | - Bodén M, Yuan Z and Bailey |
- | - Yuan, Z., Zhang, F., Davis, M. J., Bodén | + | - Yuan Z, Zhang F, Davis MJ, Bodén M and Teasdale |
- | - Hawkins, J. and Bodén | + | - Hawkins J and Bodén M. Detecting and sorting targeting peptides with recurrent networks and support vector machines. //Journal of Bioinformatics and Computational Biology//, 4(1), 2006. |
- | - Bodén, M. and Hawkins, J. Prediction of subcellular localisation using sequence-biased recurrent networks. // | + | - Bodén M and Hawkins J. Prediction of subcellular localisation using sequence-biased recurrent networks. // |
- | - Hawkins, J. and Bodén | + | - Hawkins J and Bodén M. The applicability of recurrent neural networks for biological sequence analysis. //IEEE/ACM Transactions on Computational Biology and Bioinformatics//, |
- | - Bodén, M. and Hawkins, J. Improved access to sequential motifs: A note on the architectural bias of recurrent networks. //IEEE Transactions on Neural Networks//. 16(2), 2005. | + | - Bodén M and Hawkins J. Improved access to sequential motifs: A note on the architectural bias of recurrent networks. //IEEE Transactions on Neural Networks//. 16(2), 2005. |
- | - Bodén, M. // | + | - Bodén M. // |
- | - Bodén, M. and Blair, A. Learning the dynamics of embedded clauses, Applied Intelligence: | + | - Bodén M and Blair A. Learning the dynamics of embedded clauses, Applied Intelligence: |
- | - Bodén, M. and Wiles, J. On learning context free and context sensitive languages, //IEEE Transactions on Neural Networks//. 13(2), pp. 491-493, 2002. | + | - Bodén M and Wiles J. On learning context free and context sensitive languages, //IEEE Transactions on Neural Networks//. 13(2), pp. 491-493, 2002. |
- | - Bodén, M. and Wiles, J., Context-free and context-sensitive dynamics in recurrent neural networks, // | + | - Bodén M and Wiles J. Context-free and context-sensitive dynamics in recurrent neural networks, // |
- | - Bodén, M. and Niklasson, L., Semantic systematicity and context in connectionist Networks, // | + | - Bodén M and Niklasson L. Semantic systematicity and context in connectionist Networks, // |
==== Refereed conference papers (since 2000) ==== | ==== Refereed conference papers (since 2000) ==== |