Search results
4 maj 2024 · The proposed method predicts distance maps with a mean absolute error ( MAE) of 2.32Å and a root mean squared error ( RMSE) of 3.63Å on novel proteins. It predicts residue–residue distances more accurately than state-of-the-art structure prediction methods (ESMFold) with 3.74‰ inference time of it.
By finding recombination frequencies for many gene pairs, we can make linkage maps that show the order and relative distances of the genes on the chromosome.
23 paź 2013 · We suggest based on the dramatic improvements for the S. cerevisiae PPI network that DSD values be used in place of ordinary distance when using network information to predict protein function, either using the PPI network alone, or as part of a modern integrative function prediction method that includes data from a variety of sources beyond ...
14 lut 2024 · We have developed DeepGO-SE, a protein function prediction method which predicts functions from protein sequences using a pretrained large protein language model combined with a...
7 lip 2011 · To study the protein structure–function relationship, we propose a method to efficiently create three-dimensional maps of structure space using a very large dataset of > 30,000 Structural Classification of Proteins (SCOP) domains.
25 sty 2008 · The functional distance D f defined from the Functional Tree allows a new quantitative analysis of the functional relationship between gene products. To assess D f as a functional similarity measure we correlated sequence and annotated function similarity over a set of aligned pairs of yeast proteins.
24 sty 2014 · Distances are evaluated on a number of different scenarios including clustering of cancer tissues and genes from short time-series expression data, the two main clustering applications in gene expression.
