Computational Biology

Displaying 1 - 8 of 8CSV
Orouji, S., Liu, M. C., Korem, T., & Peters, M. A. K. (2024). Domain adaptation in small-scale and heterogeneous biological datasets. Science Advances, 10(51). https://doi.org/10.1126/sciadv.adp6040
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Miao, Y., Xu, H., & Wang, S. (2024). PartIES: a disease subtyping framework with Partition-level Integration using diffusion-Enhanced Similarities from multi-omics Data. Briefings in Bioinformatics, 26(1). https://doi.org/10.1093/bib/bbae609
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Andersen, G. T., Ianevski, A., Resell, M., Pojskic, N., Rabben, H.-L., Geithus, S., Kodama, Y., Hiroyuki, T., Kainov, D., Grønbech, J. E., Hayakawa, Y., Wang, T. C., Zhao, C.-M., & Chen, D. (2024). Multi-bioinformatics revealed potential biomarkers and repurposed drugs for gastric adenocarcinoma-related gastric intestinal metaplasia. Npj Systems Biology and Applications, 10(1). https://doi.org/10.1038/s41540-024-00455-0
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Sullivan, J. A., Spillmann, R. C., Schoch, K., Walley, N., Alkelai, A., Stong, N., Shea, P. R., Petrovski, S., Jobanputra, V., McConkie‐Rosell, A., & Shashi, V. (2023). The best of both worlds: Blending cutting‐edge research with clinical processes for a productive exome clinic. Clinical Genetics, 105(1), 62–71. Portico. https://doi.org/10.1111/cge.14437
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He, B., Wang, K., Xiang, J., Bing, P., Tang, M., Tian, G., Guo, C., Xu, M., & Yang, J. (2022). DGHNE: network enhancement-based method in identifying disease-causing genes through a heterogeneous biomedical network. Briefings in Bioinformatics, 23(6). https://doi.org/10.1093/bib/bbac405
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Dhombres, F., Morgan, P., Chaudhari, B. P., Filges, I., Sparks, T. N., Lapunzina, P., Roscioli, T., Agarwal, U., Aggarwal, S., Beneteau, C., Cacheiro, P., Carmody, L. C., Collardeau‐Frachon, S., Dempsey, E. A., Dufke, A., Duyzend, M. H., el Ghosh, M., Giordano, J. L., Glad, R., … Robinson, P. N. (2022). Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology. American Journal of Medical Genetics Part C: Seminars in Medical Genetics, 190(2), 231–242. Portico. https://doi.org/10.1002/ajmg.c.31989
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