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    An in silico study of how histone tail conformation affects the binding affinity of ING family proteins
    (Peerj Inc, 2022) Gül, Nadir; Yildiz, Ahmet
    Background. Due to its intrinsically disordered nature, the histone tail is conformationally heterogenic. Therefore, it provides specific binding sites for different binding proteins or factors through reversible post-translational modifications (PTMs). For instance, experimental studies stated that the ING family binds with the histone tail that has methylation on the lysine in position 4. However, numerous complexes featuring a methylated fourth lysine residue of the histone tail can be found in the UniProt database. So the question arose if other factors like the conformation of the histone tail affect the binding affinity. Methods. The crystal structure of the PHD finger domain from the proteins ING1, ING2, ING4, and ING5 are docked to four histone H3 tails with two different conformations using Haddock 2.4 and ClusPro. The best four models for each combination are selected and a two-sample t-test is performed to compare the binding affinities of helical conformations vs. linear conformations using Prodigy. The proteinprotein interactions are examined using LigPlot. Results. The linear histone conformations in predicted INGs-histone H3 complexes exhibit statistically significant higher binding affinity than their helical counterparts (confidence level of 99%). The outputs of predicted models generated by the molecular docking programs Haddock 2.4 and ClusPro are comparable, and the obtained proteinprotein interaction patterns are consistent with experimentally confirmed binding patterns. Conclusion. The results show that the conformation of the histone tail is significantly affecting the binding affinity of the docking protein. Herewith, this in silico study demonstrated in detail the binding preference of the ING protein family to histone H3 tail. Further research on the effect of certain PTMs on the final tail conformation and the interaction between those factors seem to be promising for a better understanding of epigenetics.
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    Design of a Mobile Data Collection Robot for Learning-based Localization and Autonomous Driving
    (Institute of Electrical and Electronics Engineers Inc., 2023) Baykar, Ali Omer; Lambrecht, Jens; Kural, Ayhan; Uygur, Selcuk Eray; Yildiz, Ahmet
    This study introduces a mobile robot capable of collecting position and corresponding visual data seamlessly from both indoor and outdoor settings within the same sequence. The mobile robot has been specifically designed to navigate obstacles such as stairs and steps during transitions between indoor and outdoor environments. To accomplish this, the robot incorporates differential driving dynamics and is equipped with essential sensors including two stereo cameras, LIDAR, IMU, and GNSS. The entire system operates on the Robot Operating System (ROS). Consequently, it becomes possible to create a comprehensive dataset that encompasses not only the routes traversed by mobile vehicles but also includes all vehicle and pedestrian roads, as well as indoor spaces, found within a campus environment. © 2023 IEEE.
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    Spatio-temporal pedestrian accident analysis to improve urban pedestrian safety: The case of the eskişehir motorway
    (Gazi Universitesi, 2015) Kaygisiz, Ömür; Yildiz, Ahmet; Düzgün, Şebnem
    Determining pedestrian accident hotspots on road segments is a crucial part of the pedestrian safety assessment as it is used to prioritize problematic parts of a road network for in particularly planning and implementation strategies. Moreover, the spatial pattern of the pedestrian accidents may change over time due to several factors. In order to better understand pedestrian safety conditions, pedestrian accident patterns have to be analysed with regard to both space and time. This paper adapts such a spatio-temporal hotspot detection method for the analysis of pedestrian accidents. In this study, 189 traffic accidents involving pedestrians that resulted in injury or fatality on the Eskişehir Motorway (Turkey) between the years of 2005 and 2010 are mapped with their spatial and temporal information. Network-based Kernel Density Estimation is used to examine the hotspots of pedestrian accidents and their changes over the years. Then, the significances of the results are evaluated by using Network-based the Nearest Neighbor Distance and the K-function methods. The impact of land use change and taken measures are evaluated based on spatio-temporal hotspot analysis. © 2015, Gazi University Eti Mahallesi. All rights reserved.