iDLB-Pred:使

Sharaf J Malebary1, Nashwan Alromema2

  • 1Department of Information Technology, Faculty of Computing and Information Technology-Rabigh, King Abdulaziz University, P.O. Box 344, 21911, Rabigh, Saudi Arabia. smalebary@kau.edu.sa.

Scientific reports
|October 21, 2024
PubMed
概括

预测蛋白质中的脂质结合残留物对于理解生物过程和疾病至关重要. 新的iDLB-Pred工具使用深度学习来准确地从蛋白质序列中识别这些无序的脂质结合残留物 (DLBRs).