Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction

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    G. Pavithrra, Ramalingam Rajasekaran · 2018 · Interdisciplinary Sciences Computational Life Sciences
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    Ye Sun Han, Simin Zhang, Fei He · 2023 · Mathematics
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    Yufeng Liu, Haipeng Gong · 2012 · Biophysical Journal
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    Armando D. Solis, Shalom R. Rackovsky · 2009 · Proteins Structure Function and Bioinformatics
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    Michael Fernández, Leyden Fernández, Pedro Sánchez, Julio Caballero, José Ignacio Abreu · 2008 · Molecular Simulation
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    Avishek Kumar, Paul Campitelli, Michael F. Thorpe, Sefika Banu Ozkan · 2015 · Proteins Structure Function and Bioinformatics
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    Md. Anowar Hossain, Hairul Azman Roslan, Md. Rezaul Karim, Yoshinobu Kimura · 2016 · International Journal of Bioinformatics Research and Applications
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    Jun Pei, Lin Frank Song, Kenneth M. Merz · 2020 · Journal of Chemical Theory and Computation
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    Patrick M. Buck, Christopher Bystroff · 2008 · Proteins Structure Function and Bioinformatics
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    Shashi Bhushan Pandit, Hongyi Zhou, Jeffrey Skolnick · 2010
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    Andreas Hildebrandt, Oliver Kohlbacher, Hans‐Peter Lenhof · 2007
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    Liam James McGuffin · 2010 · Wiley eBooks
28. Protein structure selection based on consensus
    Qingguo Wang, Yi Shang, Dong He Xu · 2010 · IEEE Congress on Evolutionary Computation (CEC)
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    Shruti Agrawal, Pralay Mitra · 2024 · Wiley eBooks
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    Karolina Smolińska, Marcin Pacholczyk · 2017 · Biology Direct
31. Diverse effects of distance cutoff and residue interval on the performance of distance-dependent atom-pair potential in protein structure prediction
    Yuangen Yao, Rong Gui, Quan Liu, Ming Yi, Haiyou Deng · 2017 · BMC Bioinformatics
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    Charles W. Christoffer, Yuki Kagaya, Jacob C. Verburgt, Genki Terashi, Woong‐Hee Shin, Anika Jain, Daipayan Sarkar, Tunde W. Aderinwale, Sai Raghavendra Maddhuri Venkata Subramaniya, Xiao Wang et al. · 2025 · Proteins Structure Function and Bioinformatics
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    Emil Stefańczyk, Agata Mitura, Marta Utratna, Magdalena Maria Staniszewska · 2025 · Computational and Structural Biotechnology Journal
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    Jiong Zhang, Bogdan Barz, Jingfen Zhang, Dong He Xu, Ioan Kosztin · 2015 · Proteins Structure Function and Bioinformatics
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    Guillaume Launay, Thomas Simonson · 2010 · Journal of Computational Chemistry
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    Xin Gao, Jinbo Xu, Shuai Cheng Li, Ming Li · 2009 · Journal of Bioinformatics and Computational Biology
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    Federico Campeotto, Alessandro Dal Palù, Agostino Dovier A, Ferdinando Fioretto, Enrico Pontelli · 2012 · Lecture notes in computer science
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    John E. Holland, Gevorg Grigoryan · 2022 · Protein Science
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    Michael A. Johnston, Jens Erik Nielsen · 2011 · Annual reports in computational chemistry
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    Peter Røgen, Patrice Koehl · 2013 · Proteins Structure Function and Bioinformatics
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    Jian Ping Xie, Pengwei Zhang, Chuanjiang Li, Qianhua Huang, Rong Zhou, Tao Peng · 2011 · Gene
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    Qingguo Wang, CHARLES SHANG, Dong He Xu, Yi Shang · 2013 · International Journal of Artificial Intelligence Tools
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    Matsuyuki Shirota, Takashi Ishida, Kengo Kinoshita · 2009 · Protein Science
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    Sandeep Chakraborty, Ravindra Venkatramani, Basuthkar Jagadeeshwar Rao, Bjarni Ásgeirsson, Abhaya M. Dandekar · 2013 · F1000Research
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    Akanksha Gupta, Rahul Agarwal, Ashutosh Singh, Sonika Bhatnagar · 2016 · Journal of Receptors and Signal Transduction
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    Sandeep Chakraborty, Ravindra Venkatramani, Basuthkar Jagadeeshwar Rao, Bjarni Ásgeirsson, Abhaya M. Dandekar · 2013 · F1000Research
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    Junlin Wang, Wenbo Wang, Yi Shang, Dong He Xu · 2022 · IEEE International Conference on Cognitive Machine Intelligence (CogMI)
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    Michael S. Lee, In‐Chul Yeh, Nela Zavaljevski, Paul Wilson, Jaques Reifman A · 2006
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    Marie Le Naour—Vernet, Florian Charriat, Jérôme Gracy, Sandrine Cros‐Arteil, Sébastien Ravel, Florian Veillet, Isabelle Meusnier, André Padilla, Thomas Kroj, Stella Césari et al. · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
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    Ambrosetti, F., Jiménez-García, B., Roel-Touris, J., Bonvin, A.M.J.J. · 2019 · SSRN Electronic Journal
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    Sung‐Ling Tang, Maryam Rachmawati Sumitra, Lung-Ching Chen, Feng‐Cheng Liu, Han-Lin Hsu, Yu‐Cheng Kuo, Muhamad Ansar, Sheng‐Liang Huang, Shih‐Yu Lee, Hong-Jaan Wang et al. · 2025 · Computers in Biology and Medicine
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    Phillip Vo, Daniel E. Connors, Brendan P. Sharkey, Stephen A. Gravina, Guy Servant, Chase T. McFarland, Tyler T. Pitkanen, Christopher D. Burk, Chloe P. Cowen, Elizabeth Grein et al. · 2026 · Biochemistry
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    Daniel Holtby, Shuai Cheng Li, Ming Li · 2012 · Lecture notes in computer science
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    Kiyoto Aramis Tanemura, Jun Pei, Kenneth M. Merz · 2020 · Proteins Structure Function and Bioinformatics
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    Shruti Sunil Ranade, Ramalingam Rajasekaran · 2020 · Molecular Simulation
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    Maciej Błaszczyk, Dominik Gront, Sebastian Kmiecik, Katarzyna Ziółkowska, Marta Panek, Andrzej Koliński · 2013 · Springer series in bio-/neuroinformatics
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    Shinji Tokuhiro, Mitsuru Nagataki, Blanca R. Jarilla, Kouji Uda, Tomohiko Suzuki, Tetsuro Sugiura, Takeshi Agatsuma · 2014 · Molecular and Biochemical Parasitology
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    Yaohang Li, Weihang Zhu · 2010 · IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum
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    Matsuyuki Shirota, Takashi Ishida, Kengo Kinoshita · 2011 · Proteins Structure Function and Bioinformatics
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    Gareth Haydn Williams, Andrew Toon · 2010 · Protein Science
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    Guijun Zhao, Hui Juan Lu · 2005 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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    Ruben Acuña, Zoé Lacroix, Jacques Chomilier · 2012 · IEEE World Congress on Services (SERVICES)
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    Xiaoyang Jing, Qiwen Dong, Xuan Liu, Bin Liu · 2015 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
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    Wenyi Qin, Guijun Zhao, Matthew B. Carson, Caiyan Jia, Hui Juan Lu · 2015 · IET Systems Biology
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    Marcin Pacholczyk, Karolina Smolińska, Marta Iwanaszko, Marek Kimmel · 2014 · IWBBIO
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    Nicoletta Ceres, Richard Lavery · 2012 · Royal Society of Chemistry eBooks
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    Hao Fan · 2013
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    Majid Masso, Iosif I. Vaisman · 2010
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    Samuel W. K. Wong · 2013 · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
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    Nan Jiang, W. XinyuWu, Ian G. Mitchell · 2005 · Soft Computing
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    Hocine Madaoui, E. Becker, Raphaël Guérois · 2006 · Humana Press eBooks
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    Brian Matthews · 2017 · Protein Science
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