Autor: Plewczynski, Dariusz - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Role of the host genetic variability in the influenza A virus susceptibility
Autorzy:: Arcanjo, Ana
Mazzocco, Giovanni
de Oliveira, Silviene
Plewczynski, Dariusz
Radomski, Jan
Powiązania:: https://bibliotekanauki.pl/articles/1039238.pdf
Data publikacji:: 2014
Wydawca:: Polskie Towarzystwo Biochemiczne
Tematy:: Influenza A virus
host-pathogen interactions
Opis:: The aftermath of influenza infection is determined by a complex set of host-pathogen interactions, where genomic variability on both viral and host sides influences the final outcome. Although there exists large body of literature describing influenza virus variability, only a very small fraction covers the issue of host variance. The goal of this review is to explore the variability of host genes responsible for host-pathogen interactions, paying particular attention to genes responsible for the presence of sialylated glycans in the host endothelial membrane, mucus, genes used by viral immune escape mechanisms, and genes particularly expressed after vaccination, since they are more likely to have a direct influence on the infection outcome.
Źródło:: Acta Biochimica Polonica; 2014, 61, 3; 403-419
0001-527X
Pojawia się w:: Acta Biochimica Polonica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Comparison of proteins based on segments structural similarity.
Autorzy:: Plewczynski, Dariusz
Pas, Jakub
von Grotthuss, Marcin
Rychlewski, Leszek
Powiązania:: https://bibliotekanauki.pl/articles/1043336.pdf
Data publikacji:: 2004
Wydawca:: Polskie Towarzystwo Biochemiczne
Tematy:: 3D-hit
protein structure comparison
liveBench
protein structure
toolShop
structural hashing
Opis:: We present here a simple method for fast and accurate comparison of proteins using their structures. The algorithm is based on structural alignment of segments of Ca chains (with size of 99 or 199 residues). The method is optimized in terms of speed and accuracy. We test it on 97 representative proteins with the similarity measure based on the SCOP classification. We compare our algorithm with the LGscore2 automatic method. Our method has the same accuracy as the LGscore2 algorithm with much faster processing of the whole test set, which is promising. A second test is done using the ToolShop structure prediction evaluation program and shows that our tool is on average slightly less sensitive than the DALI server. Both algorithms give a similar number of correct models, however, the final alignment quality is better in the case of DALI. Our method was implemented under the name 3D-Hit as a web server at http://3dhit.bioinfo.pl/ free for academic use, with a weekly updated database containing a set of 5000 structures from the Protein Data Bank with non-homologous sequences.
Źródło:: Acta Biochimica Polonica; 2004, 51, 1; 161-172
0001-527X
Pojawia się w:: Acta Biochimica Polonica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Prediction of signal peptides in protein sequences by neural networks
Autorzy:: Plewczynski, Dariusz
Slabinski, Lukasz
Ginalski, Krzysztof
Rychlewski, Leszek
Powiązania:: https://bibliotekanauki.pl/articles/1040738.pdf
Data publikacji:: 2008
Wydawca:: Polskie Towarzystwo Biochemiczne
Tematy:: neural networks
protein database
protein sequences
signal peptides
Opis:: We present here a neural network-based method for detection of signal peptides (abbreviation used: SP) in proteins. The method is trained on sequences of known signal peptides extracted from the Swiss-Prot protein database and is able to work separately on prokaryotic and eukaryotic proteins. A query protein is dissected into overlapping short sequence fragments, and then each fragment is analyzed with respect to the probability of it being a signal peptide and containing a cleavage site. While the accuracy of the method is comparable to that of other existing prediction tools, it provides a significantly higher speed and portability. The accuracy of cleavage site prediction reaches 73% on heterogeneous source data that contains both prokaryotic and eukaryotic sequences while the accuracy of discrimination between signal peptides and non-signal peptides is above 93% for any source dataset. As a consequence, the method can be easily applied to genome-wide datasets. The software can be downloaded freely from http://rpsp.bioinfo.pl/RPSP.tar.gz.
Źródło:: Acta Biochimica Polonica; 2008, 55, 2; 261-267
0001-527X
Pojawia się w:: Acta Biochimica Polonica
Dostawca treści:: Biblioteka Nauki