Multidimensional persistence in biomolecular data
نویسندگان
چکیده
منابع مشابه
Multidimensional persistence in biomolecular data
Persistent homology has emerged as a popular technique for the topological simplification of big data, including biomolecular data. Multidimensional persistence bears considerable promise to bridge the gap between geometry and topology. However, its practical and robust construction has been a challenge. We introduce two families of multidimensional persistence, namely pseudomultidimensional pe...
متن کاملMultidimensional Persistence and Noise
In this paper we study multidimensional persistence modules [5, 13] via what we call tame functors and noise systems. A noise system leads to a pseudo-metric topology on the category of tame functors. We show how this pseudo-metric can be used to identify persistent features of compact mul-tidimensional persistence modules. To count such features we introduce the feature counting invariant and ...
متن کاملComputing Multidimensional Persistence
The theory of multidimensional persistence captures the topology of a multifiltration – a multiparameter family of increasing spaces. Multifiltrations arise naturally in the topological analysis of scientific data. In this paper, we give a polynomial time algorithm for computing multidimensional persistence. We recast this computation as a problem within computational commutative algebra and ut...
متن کاملInvariants for Multidimensional Persistence
The amount of data that our digital society collects is unprecedented. This represents a valuable opportunity to improve our quality of life by gaining insights about complex problems related to neuroscience, medicine and biology among others. Topological methods, in combination with classical statistical ones, have proven to be a precious resource in understanding and visualizing data. Multidi...
متن کاملMultidimensional Langevin modeling of biomolecular dynamics.
A systematic computational approach to describe the conformational dynamics of biomolecules in reduced dimensionality is presented. The method is based on (i) the decomposition of a high-dimensional molecular dynamics trajectory into a few "system" and (many) "bath" degrees of freedom and (ii) a Langevin simulation of the resulting model. Employing principal component analysis, the dimension of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computational Chemistry
سال: 2015
ISSN: 0192-8651
DOI: 10.1002/jcc.23953