An Abnormal Gene Detection Method Based on Selene

Author:

Zhang Qiang,Jiang Yizhang

Publisher

Springer International Publishing

Reference23 articles.

1. Shen, Y., et al.: Global profile of tRNA-derived small RNAs in gastric cancer patient plasma and identification of tRF-33-P4R8YP9LON4VDP as a new tumor suppressor. Int. J. Med. Sci. 18(7), 1570–1579 (2021)

2. Jabbar, M.A., Abraham, A., Dogan, O., Madureira, A.M., Tiwari, S.: Deep Learning in Biomedical and Health Informatics: Current Applications and Possibilities. CRC Press, Boca Raton (2021)

3. Eid, S.A., et al.: Gene expression profiles of diabetic kidney disease and neuropathy in eNOS knockout mice: predictors of pathology and RAS blockade effects. FASEB J. Official Publ. Fed. Am. Soc. Exp. Biol. 35(5), e21467 (2021)

4. Chen, K.M., Cofer, E.M., Zhou, J., Troyanskaya, O.G.: Selene: a PyTorch-based deep learning library for sequence data. Nat. Methods Tech. Life Sci. Chemists 16(4), 315–318 (2019)

5. Camacho, D.M., Collins, K.M., Powers, R.K., Costello, J.C., Collins, J.J.: Next-generation machine learning for biological networks. Cell 173(7), 1581–1592 (2018)

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