Drug–target interactionsFeature extractionProtein domainsSparse modelingMost drugs produce their phenotypic effects by interacting with target proteins, and understanding the molecular features that underpin drug–target interactions is crucial when designing a novel......
Psicov: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments. Bioinformatics. 2012;28(2):184–90. Article CAS PubMed Google Scholar Davis MI, Hunt JP, Herrgård S, Ciceri P, Wodicka LM, Pallares G, Hocker M, Treiber DK, Zarr...
A target space object is deemed cooperative if it is built to provide information suitable for the estimation of its pose with respect to the chaser. Also, it can be actively or passively cooperative depending on whether it interacts with a dedicated radio-link with the chaser, or not. Cooper...
The authors in [11] used generalized recurrent neural networks to obtain the position estimation of moving targets in two-dimensional scenes, and then used the Kalman filter framework to improve the estimated value for achieving the prediction of the target trajectory. In [12], based on geometric...
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& Yun, Y. Detection and estimation algorithm for marine target with micromotion based on adaptive sparse modified-lv’s transform. IEEE Trans. Geosci. Remote Sens. 60, 1–17 (2022). Google Scholar Gao, C., Tao, R. & Kang, X. Weak target detection in the presence of sea clutter ...
In that direction, owing to the disadvantage of in vivo estimation as time consuming and expensive, in silico methods have become inevitable approaches. In this study, we used a graph-based signature method namely, pkCSM for the prediction of pharmacokinetic and toxicity properties of the compounds...
Partial AUC estimation and regression. Biometrics. 2003;59(3):614–23. Article PubMed Google Scholar Chang CC, Lin CJ. LIBSVM: a library for support vector machines. Acm Trans Intell Syst Technol. 2007;2(3):389–96. Google Scholar Gönen M. Predicting drug–target interactions from ...
Mlk smart corridor: An urban testbed for smart city applications. In 2019 IEEE international conference on big data (Big Data) (pp. 3506–3511). IEEE Hassan, Y., Zhao, J., Harris, A., & Sartipi, M.(2023). Deep learning-based framework for traffic estimation for the mlk smart ...
Meanwhile, considering that different singular values have different importance, we use the WSWTNN regularization for more accurate background estimation. (3) To find the solution of the proposed WSWTNN-PnP method, we design an algorithm based on alternating direction multiplier method (ADMM) to ...