Azim, Sayed Mehedi, Sabab, Noor_Hossain Nuri, Noshadi, Iman, Alinejad-Rokny, Hamid, Sharma, Alok, Shatabda, Swakkhar, and Dehzangi, Iman. Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers. Retrieved from https://par.nsf.gov/biblio/10533995. Informatics in Medicine Unlocked 42.C Web. doi:10.1016/j.imu.2023.101348.

Azim, Sayed Mehedi, Sabab, Noor_Hossain Nuri, Noshadi, Iman, Alinejad-Rokny, Hamid, Sharma, Alok, Shatabda, Swakkhar, & Dehzangi, Iman. Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers. Informatics in Medicine Unlocked, 42 (C). Retrieved from https://par.nsf.gov/biblio/10533995. https://doi.org/10.1016/j.imu.2023.101348

Azim, Sayed Mehedi, Sabab, Noor_Hossain Nuri, Noshadi, Iman, Alinejad-Rokny, Hamid, Sharma, Alok, Shatabda, Swakkhar, and Dehzangi, Iman. "Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers". Informatics in Medicine Unlocked 42 (C). Country unknown/Code not available: Elsevier. https://doi.org/10.1016/j.imu.2023.101348. https://par.nsf.gov/biblio/10533995.

@article{osti_10533995,
place = {Country unknown/Code not available}, title = {Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers}, url = {https://par.nsf.gov/biblio/10533995}, DOI = {10.1016/j.imu.2023.101348}, abstractNote = {}, journal = {Informatics in Medicine Unlocked}, volume = {42}, number = {C}, publisher = {Elsevier}, author = {Azim, Sayed Mehedi and Sabab, Noor_Hossain Nuri and Noshadi, Iman and Alinejad-Rokny, Hamid and Sharma, Alok and Shatabda, Swakkhar and Dehzangi, Iman}, }