The visualization of multidimensional energy landscapes is important, providing insight into the kinetics and thermodynamics of a system, as well the range of structures a system can adopt. It is, however, highly nontrivial, with the number of dimensions required for a faithful reproduction of the landscape far higher than can be represented in two or three dimensions. Metric disconnectivity graphs provide a possible solution, incorporating the landscape connectivity information present in disconnectivity graphs with structural information in the form of a metric. In this study, we present a new software package, PyConnect, which is capable of producing both disconnectivity graphs and metric disconnectivity graphs in two or three dimensions. We present as a test case the analysis of the 69-bead BLN coarse-grained model protein and show that, by choosing appropriate order parameters, metric disconnectivity graphs can resolve correlations between structural features on the energy landscape with the landscapes energetic and kinetic properties.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285870 | PMC |
| http://dx.doi.org/10.1002/jcc.23643 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Modularity-based mathematical modeling of ligand inter-nanocluster connectivity for unraveling reversible stem cell regulation.
Nat Commun
December 2024
Department of Materials Science and Engineering, Korea University, Seoul, Republic of Korea.
The native extracellular matrix is continuously remodeled to form complex interconnected network structures that reversibly regulate stem cell behaviors. Both regulation and understanding of its intricate dynamicity can help to modulate numerous cell behaviors. However, neither of these has yet been achieved due to the lack of designing and modeling such complex structures with dynamic controllability.
View Article and Find Full Text PDFPatterns of Social Connection Among Older Adults in England.
JAMA Netw Open
December 2024
Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, United Kingdom.
Importance: Issues related to social connection are increasingly recognized as a global public health priority. However, there is a lack of a holistic understanding of social connection and its health impacts given that most empirical research focuses on a single or few individual concepts of social connection.
Objective: To explore patterns of social connection and their associations with health and well-being outcomes.
Integrating clinical knowledge into AI remains challenging despite numerous medical guidelines and vocabularies. Medical codes, central to healthcare systems, often reflect operational patterns shaped by geographic factors, national policies, insurance frameworks, and physician practices rather than the precise representation of clinical knowledge. This disconnect hampers AI in representing clinical relationships, raising concerns about bias, transparency, and generalizability.
View Article and Find Full Text PDFAltered topology in cortical morphometric similarity network in recurrent major depressive disorder.
J Psychiatr Res
November 2024
Neuropsychiatry Imaging Center, Department of Radiology, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, Guangdong, 518020, China. Electronic address:
Background: Recurrent major depressive disorder (RDD) is increasingly understood to be associated with a 'disconnection' within the brain areas. But, the true understanding of cortical connectivities remains challenging. Morphometric similarity network (MSN) with multi-modal magnetic resonance imaging (MRI) could provide more information about cortical micro-architecture changes in individuals with RDD.
View Article and Find Full Text PDFMoral Association Graph: A Cognitive Model for Automated Moral Inference.
Top Cogn Sci
November 2024
Department of Computer Science, University of Toronto.
Automated moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach typically relies on language models to infer moral relevance or moral properties of a concept. This approach demands complex parameterization and costly computation, and it tends to disconnect with existing psychological accounts of moralization.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!