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The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools
CLUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W. The new system is easy to use, providing an integrated system...
The Protein Data Bank
The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB...
An Inventory for Measuring Depression
The difficulties inherent in obtaining consistent and adequate diagnoses for the purposes of research and therapy have been pointed out by a number of authors. Pasamanick<sup>12...
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Systematic reviews and meta-analyses have become increasinglyimportant in health care. Clinicians readthem to keep up to date with their field (1, 2), and they areoften used as ...
MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms
The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation o...
Equation of State Calculations by Fast Computing Machines
A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is ...
Matplotlib: A 2D Graphics Environment
Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operat...
Adaptation in Natural and Artificial Systems
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learn...
Fully convolutional networks for semantic segmentation
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...