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Yuan, Y., Bayer, P. E., Batley, J., & Edwards, D. (2017). Improvements in genomic technologies: application to crop genomics. Trends in Biotechnology.Search in Google Scholar
Laura, G. A., Koonin, E. V., & Kristensen, D. M. (2017). Prokaryotic virus orthologous groups (pvogs): a resource for comparative genomics and protein family annotation. Nucleic Acids Research, D491.Search in Google Scholar
Nielsen, Rasmus, Willerslev, Eske, Pritchard, & Jonathan, et al. (2017). Tracing the peopling of the world through genomics. Nature.Search in Google Scholar
Consortium, P. G. (2018). Computational pan-genomics: status, promises and challenges. Briefings in Bioinformatics(1), 118-135.Search in Google Scholar
Ferenci, T. (2019). Irregularities in genetic variation and mutation rates with environmental stresses. Environmental Microbiology, 21(11).Search in Google Scholar
Dockhorn, A., & Lucas, S. (2022). Choosing representation, mutation, and crossover in genetic algorithms. IEEE computational intelligence magazine.Search in Google Scholar
Amadou, A., Praud, D., Coudon, T., Deygas, F., Grassot, L., & Dubuis, M., et al. (2023). Long-term exposure to nitrogen dioxide air pollution and breast cancer risk: a nested case-control within the french e3n cohort study. Environmental Pollution.Search in Google Scholar
Mao, X., He, W., Eriksson, M., Lindstrm, L., Holowko, N., & Lagercrantz, S., et al. (2022). 133p using breast cancer risk factors of women to estimate incidence of breast cancer in their sisters. Annals of Oncology.Search in Google Scholar
Dhiman, D., & Kumar, A. (2021). Association of preoperative serum adipokines, insulin and sex steroid hormones with breast cancer risk in the indian women. Indian Journal of Cancer.Search in Google Scholar
Morana, G., Tortora, D., Serena Staglianò, Nozza, P., Mascelli, S., & Severino, M., et al. (2018). Pediatric astrocytic tumor grading: comparison between arterial spin labeling and dynamic susceptibility contrast mri perfusion. Neuroradiology.Search in Google Scholar
Boddaert, Nathalie, Dangouloff-Ros, & Volodia. (2017). Arterial spin labeling to predict brain tumor grading: limits of cutoff cerebral blood flow values response. Radiology.Search in Google Scholar
Kryvenko, O. N., Epstein, J. I., Ali, M., Iakymenko, O. A., Almeida, E. S. R. D., & Kumar, C. D., et al. (2024). Radical prostatectomy cancer grade and percentage of gleason pattern 4 estimated by global vs individual tumor grading correlate differently with the risk of biochemical recurrence in grade group 2 and 3 cancers. American Journal of Clinical Pathology.Search in Google Scholar
Bruckmann, N. M., Rischpler, C., Kirchner, J., Umutlu, L., Herrmann, K., & Ingenwerth, M., et al. (2021). Correlation between contrast enhancement, standardized uptake value (suv), and diffusion restriction (adc) with tumor grading in patients with therapy-naive neuroendocrine neoplasms using hybrid ga-68-dotatoc pet/mri. European Journal of Radiology(137-), 137.Search in Google Scholar
Zille, P., Calhoun, V. D., & Wang, Y. P. (2017). Enforcing co-expression within a brain-imaging genomics regression framework. IEEE Transactions on Medical Imaging, PP(99), 1-1.Search in Google Scholar
Cen, X., Dong, W., Lv, W., Zhao, Y., Dubee, F., & Mentis, A. F. A., et al. (2024). Towards interpretable imaging genomics analysis: methodological developments and applications. Information Fusion, 102.Search in Google Scholar
Gossmann, A., Zille, P., Calhoun, V., & Wang, Y. P. (2017). Fdr-corrected sparse canonical correlation analysis with applications to imaging genomics. IEEE Transactions on Medical Imaging.Search in Google Scholar
Shih, Robert, Y., Koeller, Kelly, & K. (2018). Imaging genomics of embryonal tumors of the central nervous system responds. Radiographics, 38(4), 1286-1286.Search in Google Scholar
Mollaei, P., & Farimani, A. B. (2023). Global machine learning model predicting activity level of any gpcrs based on protein structure. Biophysical journal, 122 3S1, 181a.Search in Google Scholar
GuYuanlin, LiBaihua, & MengQinggang. (2022). Hybrid interpretable predictive machine learning model for air pollution prediction. Neurocomputing(468-Jan.11).Search in Google Scholar
Jen, K. Y., Albahra, S., Yen, F., Sageshima, J., & Rashidi, H. H. (2021). Automated en masse machine learning model generation shows comparable performance as classic regression models for predicting delayed graft function in renal allografts. Transplantation.Search in Google Scholar
Shepherdson, M., Kilburn, D., Ullah, S., Price, T., Karapetis, C. S., & Nguyen, P., et al. (2023). Survival outcomes for patients with colorectal cancer with synchronous liver only metastasis. ANZ journal of surgery.Search in Google Scholar
Ito, D., Yogosawa, S., Mimoto, R., Hirooka, S., & Yoshida, K. (2017). Dyrk2 is a suppressor and potential prognostic marker for liver metastasis of colorectal cancer. Cancer Science, 108(8).Search in Google Scholar
Shin, S., Choi, C. W., Moon, J. M., Kim, H. S., & Choi, C. H. (2021). P150 histologic features predicting prognosis and their relationship with endoscopic findings in ulcerative colitis patients with mucosal healing. Journal of Crohn's and Colitis(Supplement_1), Supplement_1.Search in Google Scholar
Basu, S., Sussman, J. B., & Hayward, R. A. (2017). Detecting heterogeneous treatment effects to guide personalized blood pressure treatment. Annals of Internal Medicine.Search in Google Scholar
Celik, S., Gokbayrak, O., Erol, A., Yorukoglu, K., Aktas, T., & Sari, H., et al. (2023). Anna karenina principle in personalized treatment of bladder cancer according to oncogram: which drug for which patient?. Personalized medicine(2), 20.Search in Google Scholar
Yi, Du, Hirohito, Yamaguchi, Jennifer, & L., et al. (2017). Parp inhibitors as precision medicine for cancer treatment. National Science Review.Search in Google Scholar
Nazha, A., & Sekeres, M. A. (2017). Precision medicine in myelodysplastic syndromes and leukemias: lessons from sequential mutations. Annual Review of Medicine, 68(1), 127.Search in Google Scholar
Schütte, Moritz, Ogilvie, L. A., Rieke, D. T., Lange, B. M. H., Yaspo, M. L., & Lehrach, H. (2017). Cancer precision medicine: why more is more and dna is not enough. Public Health Genomics, 20(2), 70-80.Search in Google Scholar
Bush, & Andrew. (2017). Translating asthma: dissecting the role of metabolomics, genomics and personalized medicine. Indian Journal of Pediatrics.Search in Google Scholar
Tsoli, M., Wadham, C., Pinese, M., Failes, T., & Ziegler, D. S. (2018). Abstract lb-137: integrated genomics: drug screening and personalized xenograft development approach to identify precision treatments for aggressive pediatric brain tumors. Cancer Research, 78(13 Supplement), LB-137-LB-137.Search in Google Scholar
Wang, D. R., Guadagno, C. R., Xiaowei, M., Scott, M. D., Pleban, J. R., & Baker, R. L., et al. (2019). A framework for genomics-informed ecophysiological modeling in plants. Journal of Experimental Botany(9), 9.Search in Google Scholar
Graham Rose,David J. Wooldridge,Catherine Anscombe,Edward T. Mee,Raju V. Misra & Saheer Gharbia.(2015).Challenges of the Unknown: Clinical Application of Microbial Metagenomics. International Journal of Genomics292950.Search in Google Scholar
Peter Z. Yan,Fei Wang,Nathaniel Kwok,Baxter B. Allen,Sotirios Keros & Zachary Grinspan.(2019). Automated spectrographic seizure detection using convolutional neural networks.Seizure: European Journal of Epilepsy124-131.Search in Google Scholar
KirstenMcAulay.(2024).Inducing Targeted Protein Degradation: From Chemical Biology to Drug Discovery and Clinical Applications. Edited by Philipp Cromm.ChemMedChem(7),Search in Google Scholar
Yu-Bao Zou,Ru-Tai Hui & Lei Song.(2019).The era of clinical application of gene diagnosis in cardiovascular diseases is coming.Chronic Diseases and Translational Medicine(4),214-220.Search in Google Scholar
Patil V M,Patel F D,Chakraborty S,Oinam A S & Sharma S C.(2011).Can point doses predict volumetric dose to rectum and bladder: a CT-based planning study in high dose rate intracavitary brachytherapy of cervical carcinoma?.The British journal of radiology(1001),441-8.Search in Google Scholar