PROTEIN MEASUREMENT WITH THE FOLIN PHENOL REAGENT
Since 1922 when Wu proposed the use of the Folin phenol reagent for the measurement of proteins (l), a number of modified analytical procedures ut.ilizing this reagent have been...
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Since 1922 when Wu proposed the use of the Folin phenol reagent for the measurement of proteins (l), a number of modified analytical procedures ut.ilizing this reagent have been...
Molecular Cloning has served as the foundation of technical expertise in labs worldwide for 30 years. No other manual has been so popular, or so influential. Molecular Cloning, ...
Learning to store information over extended time intervals by recurrent backpropagation takes a very long time, mostly because of insufficient, decaying error backflow. We brief...
The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and s...
The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individu...
A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, labo...
We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting,...
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 (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...
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional informatio...
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...