pyRMSD: a Python package for efficient pairwise RMSD matrix calculation and handling

نویسندگان

  • Víctor A. Gil
  • Victor Guallar
چکیده

SUMMARY We introduce pyRMSD, an open source standalone Python package that aims at offering an integrative and efficient way of performing Root Mean Square Deviation (RMSD)-related calculations of large sets of structures. It is specially tuned to do fast collective RMSD calculations, as pairwise RMSD matrices, implementing up to three well-known superposition algorithms. pyRMSD provides its own symmetric distance matrix class that, besides the fact that it can be used as a regular matrix, helps to save memory and increases memory access speed. This last feature can dramatically improve the overall performance of any Python algorithm using it. In addition, its extensibility, testing suites and documentation make it a good choice to those in need of a workbench for developing or testing new algorithms. AVAILABILITY The source code (under MIT license), installer, test suites and benchmarks can be found at https://pele.bsc.es/ under the tools section. CONTACT [email protected] SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Fast 3×N Matrix Multiply Routine for Calculation of Protein RMSD

The bottleneck for the rapid calculation of the root-mean-square deviation in atomic coordinates (RMSD) between pairs of protein structures for large numbers of conformations is the evaluation of a 3×N x N × 3 matrix product over conformation pairs. Here we describe two matrix multiply routines specialized for the 3×N case that are able to significantly outperform (by up to 3X) offthe-shelf hig...

متن کامل

Calculation of One-dimensional Forward Modelling of Helicopter-borne Electromagnetic Data and a Sensitivity Matrix Using Fast Hankel Transforms

The helicopter-borne electromagnetic (HEM) frequency-domain exploration method is an airborne electromagnetic (AEM) technique that is widely used for vast and rough areas for resistivity imaging. The vast amount of digitized data flowing from the HEM method requires an efficient and accurate inversion algorithm. Generally, the inverse modelling of HEM data in the first step requires a precise a...

متن کامل

The iisignature library: efficient calculation of iterated-integral signatures and log signatures

Iterated-integral signatures and log signatures are vectors calculated from a path that characterise its shape. They come from the theory of differential equations driven by rough paths, and also have applications in statistics and machine learning. We present algorithms for efficiently calculating these signatures, and benchmark their performance. We release the methods as a Python package.

متن کامل

Generalization of Dodgson's "Virtual Center" Method; an Efficient Method for Determinant Calculation

Charles Dodgson (1866) introduced a method to calculate matrices determinant, in asimple way. The method was highly attractive, however, if the sub-matrix or the mainmatrix determination is divided by zero, it would not provide the correct answer. Thispaper explains the Dodgson method's structure and provides a solution for the problemof "dividing by zero" called "virtua...

متن کامل

Determination of weight vector by using a pairwise comparison matrix based on DEA and Shannon entropy

The relation between the analytic hierarchy process (AHP) and data envelopment analysis (DEA) is a topic of interest to researchers in this branch of applied mathematics. In this paper, we propose a linear programming model that generates a weight (priority) vector from a pairwise comparison matrix. In this method, which is referred to as the E-DEAHP method, we consider each row of the pairwise...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Bioinformatics

دوره 29 18  شماره 

صفحات  -

تاریخ انتشار 2013