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Toplam kayıt 77, listelenen: 51-60
Perturbation-response scanning reveals key residues for allosteric control in Hsp70
(American Chemical Society, 2017)
Hsp70 molecular chaperones play-an important role in maintaining-cellular homeostasis, and are implicated in a wide array of cellular processes, including protein recovery from aggregates, cross-membrane protein translocation, ...
Regression of large-scale path loss parameters using deep neural networks
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2022)
Path loss exponent and shadowing factor are among important wireless channel parameters. These parameters can be estimated using field measurements or ray-tracing simulations, which are costly and time-consuming. In this ...
Detailed tail proteomic analysis of axolotl (Ambystoma mexicanum) using an mRNA-seq reference database
(Wiley, 2017)
Salamander axolotl has been emerging as an important model for stem cell research due to its powerful regenerative capacity. Several advantages, such as the high capability of advanced tissue, organ, and appendages ...
Modeling traders' behavior with deep learning and machine learning methods: Evidence from BIST 100 index
(Wiley-Hindawi, 2020)
Although the vast majority of fundamental analysts believe that technical analysts' estimates and technical indicators used in these analyses are unresponsive, recent research has revealed that both professionals and ...
Mood detection from physical and neurophysical data using deep learning models
(Wiley, 2019)
Nowadays, smart devices as a part of daily life collect data about their users with the help of sensors placed on them. Sensor data are usually physical data but mobile applications collect more than physical data like ...
Perturb-Scan-Pull: A novel method facilitating conformational transitions in proteins
(American Chemical Society, 2020)
Conformational transitions in proteins facilitate precise physiological functions. Therefor; it is crucial to understand the mechanisms underlying these processes to modulate protein function. Yet, studying structural and ...
SNF-NN: Computational method to predict drug-disease interactions using similarity network fusion and neural networks
(BioMed Central Ltd., 2021)
Background: Drug repositioning is an emerging approach in pharmaceutical research for identifying novel therapeutic potentials for approved drugs and discover therapies for untreated diseases. Due to its time and cost ...
Explainable artificial intelligence through graph theory by generalized social network analysis-based classifier
(Nature Portfolio, 2022)
We propose a new type of supervised visual machine learning classifier, GSNAc, based on graph theory and social network analysis techniques. In a previous study, we employed social network analysis techniques and introduced ...
The role of machine learning in identifying students at-risk and minimizing failure
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2023)
Education is very important for students' future success. The performance of students can be supported by the extra assignments and projects given by the instructors for students with low performance. However, a major ...
An efficient approach to predict eye diseases from symptoms using machine learning and ranker-based feature selection methods
(MDPI, 2023)
The eye is generally considered to be the most important sensory organ of humans. Diseases and other degenerative conditions of the eye are therefore of great concern as they affect the function of this vital organ. With ...