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Biofouling
The Journal of Bioadhesion and Biofilm Research
Volume 28, 2012 - Issue 10
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Articles

New trends in peptide-based anti-biofilm strategies: a review of recent achievements and bioinformatic approaches

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Pages 1033-1061 | Received 30 May 2012, Accepted 31 Aug 2012, Published online: 28 Sep 2012

Figures & data

Table 1. AMP sources and classes.

Figure 1. General statistics on the number of publications on AMPs (blue bars) and AMP applications to biofilms (red bars) in PubMed. The word cloud highlights research areas where these studies are most relevant.

Figure 1. General statistics on the number of publications on AMPs (blue bars) and AMP applications to biofilms (red bars) in PubMed. The word cloud highlights research areas where these studies are most relevant.

Table 2. Recent applications of AMPs in the control of biofilms.

Figure 2. Bioinformatics resources for AMP studies. MS = mass spectrometry; LC = liquid chromatography; ANNs = artificial neural networks; HMMs = hidden Markov models; QMs = quantitative matrices; SVMs = support vector machines; RFs = random forests; DA = discriminant analysis; QSAR = quantitative structure–activity relationship.

Figure 2. Bioinformatics resources for AMP studies. MS = mass spectrometry; LC = liquid chromatography; ANNs = artificial neural networks; HMMs = hidden Markov models; QMs = quantitative matrices; SVMs = support vector machines; RFs = random forests; DA = discriminant analysis; QSAR = quantitative structure–activity relationship.

Table 3. Contents and tools (similarity search, sequence alignment, prediction and others) of current AMP-related databases.

Table 4. Synergism studies involving AMPs.

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