Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
November 15, 2019International Journal of Molecular SciencesOpen Access

Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation

View Full Paper
Ask AI
Bookmark
Share

Authors

NSNalini SchaduangratMahidol UniversityCNChanin NantasenamatnLIGHT (United States)VPVirapong PrachayasittikulMahidol University

Discussion

Loading...

Member takes

Implication

Key Points

Key points are not available for this paper at this time.

Cite This Study

Schaduangrat et al. (2019) studied this question.

synapsesocial.com/papers/6a9624a231d2ffd1c13592c2https://doi.org/10.3390/ijms20225743
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Conserved Threonine Residues within the A-Loop of the Receptor NIK Differentially Regulate the Kinase Function Required for Antiviral Signaling2009 · 63 citations
  2. 2AAindex: Amino Acid Index Database1999 · 1,033 citations
  3. 3Self and viral peptides can initiate lysis by autologous natural killer cells1997 · 78 citations
  4. 4TargetAntiAngio: A Sequence-Based Tool for the Prediction and Analysis of Anti-Angiogenic Peptides2019 · 47 citations
  5. 5PAAP: A Web Server for Predicting Antihypertensive Activity of Peptides2018 · 64 citations