ELIZA

return kwic search for species out of >500 occurrences
321753 occurrences (No.65 in the rank) during 5 years in the PubMed. [no cache] 500 found

386) Here, we review the bioinformatics resources and tools available for the study of the gram-negative bacterium Pseudomonas aeruginosa, the gram-positive bacterium Staphylococcus aureus and the fungal species Candida albicans.

--- ABSTRACT ---

PMID:24106130 DOI:10.1093/bib/bbt071

2015 Briefings in bioinformatics

* Pathogenicity phenomena in three model systems: from network mining to emerging system-level properties.

- Understanding the interconnections of microbial pathogenicity phenomena, such as biofilm formation, quorum sensing and antimicrobial resistance, is a tremendous open challenge for biomedical research. Progress made by wet-lab researchers and bioinformaticians in understanding the underlying regulatory phenomena has been significant, with converging evidence from multiple high-throughput technologies. Notably, network reconstructions are already of considerable size and quality, tackling both intracellular regulation and signal mediation in microbial infection. Therefore, it stands to reason that in silico investigations would play a more active part in this research. Drug target identification and drug repurposing could take much advantage of the ability to simulate pathogen regulatory systems, host-pathogen interactions and pathogen cross-talking. Here, we review the bioinformatics resources and tools available for the study of the gram-negative bacterium Pseudomonas aeruginosa, the gram-positive bacterium Staphylococcus aureus and the fungal species Candida albicans. The choice of these three microorganisms fits the rationale of the review converging into pathogens of great clinical importance, which thrive in biofilm consortia and manifest growing antimicrobial resistance.

--- ABSTRACT END ---

[
right
kwic]

[frequency of next (right) word to species]

(1)93 null	(11)7 but	(21)3 can	(31)2 for
(2)46 of	(12)7 with	(22)3 could	(32)2 found
(3)34 in	(13)6 identification	(23)3 differences	(33)2 generated
(4)31 and	(14)5 determination	(24)3 have	(34)2 identification,
(5)19 (ROS)	(15)5 that	(25)3 level	(35)2 including
(6)18 were	(16)4 as	(26)3 may	(36)2 phytotoxicity
(7)12 is	(17)4 or	(27)2 (ROS),	(37)2 rather
(8)10 are	(18)4 to	(28)2 (overall	(38)2 such
(9)9 from	(19)4 which	(29)2 M
(10)9 was	(20)3 AEJ-89	(30)2 along

add keyword

--- WordNet output for species --- =>人類, 種, 種類 Overview of noun species The noun species has 2 senses (first 2 from tagged texts) 1. (27) species -- ((biology) taxonomic group whose members can interbreed) 2. (5) species -- (a specific kind of something; "a species of molecule"; "a species of villainy") Overview of noun specie The noun specie has 1 sense (no senses from tagged texts) 1. coinage, mintage, specie, metal money -- (coins collectively) --- WordNet end ---