Prediction of Kunitz ion channel effectors and protease inhibitors from the Ixodes ricinus sialome

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60077344%3A_____%2F14%3A00435202" target="_blank" >RIV/60077344:_____/14:00435202 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ttbdis.2014.07.016" target="_blank" >http://dx.doi.org/10.1016/j.ttbdis.2014.07.016</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ttbdis.2014.07.016" target="_blank" >10.1016/j.ttbdis.2014.07.016</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction of Kunitz ion channel effectors and protease inhibitors from the Ixodes ricinus sialome

Popis výsledku v původním jazyce

In the next generation sequencing era we are encountering hundreds of thousands of sequences from specific organisms. Such massive data must be accurately classified both functionally and structurally. Determining appropriate sequences with a specific function from next generation sequencing, however, is a daunting experimental task. A recent salivary gland transcriptome from the hard tick Ixodes ricinus, a European disease vector, has been made publicly available. Among the protein families sequenced by the salivary gland transcriptome of I. ricinus, the Kunitz-domain is one of the highly represented protein families. Thus far, recent tick transciptomes solely classify (computationally) Kunitz sequences as putative serine protease inhibitors. We present here a novel method using a machine-learning algorithm to "fish" for candidate ion-channel effectors and loss of serine protease inhibitor function within the Kunitzdomain protein family of the I. ricinus salivary gland transcriptome.

Název v anglickém jazyce

Prediction of Kunitz ion channel effectors and protease inhibitors from the Ixodes ricinus sialome

Popis výsledku anglicky

In the next generation sequencing era we are encountering hundreds of thousands of sequences from specific organisms. Such massive data must be accurately classified both functionally and structurally. Determining appropriate sequences with a specific function from next generation sequencing, however, is a daunting experimental task. A recent salivary gland transcriptome from the hard tick Ixodes ricinus, a European disease vector, has been made publicly available. Among the protein families sequenced by the salivary gland transcriptome of I. ricinus, the Kunitz-domain is one of the highly represented protein families. Thus far, recent tick transciptomes solely classify (computationally) Kunitz sequences as putative serine protease inhibitors. We present here a novel method using a machine-learning algorithm to "fish" for candidate ion-channel effectors and loss of serine protease inhibitor function within the Kunitzdomain protein family of the I. ricinus salivary gland transcriptome.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

EB - Genetika a molekulární biologie

OECD FORD obor

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Projekt

<a href="/cs/project/EE2.3.30.0032" target="_blank" >EE2.3.30.0032: Vytvoření postdoktorandských pozic na Biologickém centru AV ČR k rozvoji biologických disciplín a dosažení globální konkurenceschopnosti</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Ticks and Tick-borne Diseases

ISSN

1877-959X

e-ISSN

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Svazek periodika

5

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

4

Strana od-do

947-950

Kód UT WoS článku

000343385100052

EID výsledku v databázi Scopus

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