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# The dynamic landscape of peptide function prediction

This curated list collects peer-reviewed machine learning models
dedicated to predicting specific properties of peptides. For an
interactive and browse-able list, please visit:
<https://biogenies.info/peptide-prediction-list/>.
<!-- This curated list collects peer-reviewed machine learning models dedicated to predicting specific properties of peptides. -->

For an interactive and browse-able list, please visit:
<https://biogenies.info/amyloid-database-list/>.

- [Active](#active)
- [Non-active](#non-active)

## Active

1. A3D-MODB:
[publication](https://doi.org/https://doi.org/10.1093/nar/gkad942);
1. A3D-MODB: [publication](https://doi.org/10.1093/nar/gkad942);
[database](https://biocomp.chem.uw.edu.pl/A3D2/MODB).
2. AL-Base:
[publication](https://doi.org/https://doi.org/10.1080/13506120802676781);
2. AL-Base: [publication](https://doi.org/10.1080/13506120802676781);
[database](https://wwwapp.bumc.bu.edu/BEDAC_ALBase/).
3. AmyLoad:
[publication](https://doi.org/https://doi.org/10.1093/bioinformatics/btv375);
[publication](https://doi.org/10.1093/bioinformatics/btv375);
[database](http://comprec-lin.iiar.pwr.edu.pl/amyload/).
4. AmyloBase:
[publication](https://doi.org/https://doi.org/10.1038%2Fembor.2011.116);
4. AmyloBase: [publication](https://doi.org/10.1038%2Fembor.2011.116);
[database](http://bioserver2.sbsc.unifi.it/AmyloBase.html).
5. AmyloGraph:
[publication](https://doi.org/https://doi.org/10.1093/nar/gkac882);
5. AmyloGraph: [publication](https://doi.org/10.1093/nar/gkac882);
[database](http://amylograph.com/).
6. Amyloid Atlas 2024:
[publication](https://doi.org/https://doi.org/10.1016/j.cell.2021.08.013);
[publication](https://doi.org/10.1016/j.cell.2021.08.013);
[database](https://people.mbi.ucla.edu/sawaya/amyloidatlas/).
7. AmyPro:
[publication](https://doi.org/https://doi.org/10.1093/nar/gkx950);
7. AmyPro: [publication](https://doi.org/10.1093/nar/gkx950);
[database](http://amypro.net).
8. CARs DB:
[publication](https://doi.org/https://doi.org/10.1007/978-1-0716-3441-7_10);
8. CARs DB: [publication](https://doi.org/10.3389/fmolb.2022.882160);
[database](http://carsdb.ppmclab.com/).
9. CPAD2:
[publication](https://doi.org/https://doi.org/10.1080/13506129.2020.1715363);
9. CPAD2: [publication](https://doi.org/10.1080/13506129.2020.1715363);
[database](https://web.iitm.ac.in/bioinfo2/cpad2/index.html).
10. Cross-Beta DB:
[publication](https://doi.org/https://doi.org/10.1101/2024.02.12.579644);
[publication](https://doi.org/10.1101/2024.02.12.579644);
[database](https://crossbetadb.crbm.cnrs.fr/).
11. Fibrilizer:
[publication](https://doi.org/http://dx.doi.org/10.1016/j.bpj.2012.12.037);
[publication](http://dx.doi.org/10.1016/j.bpj.2012.12.037);
[database](https://amyloid.cs.mcgill.ca/database/index.html).
12. PrionScan:
[publication](https://doi.org/https://doi.org/10.1186/1471-2164-15-102);
12. PrionScan: [publication](https://doi.org/10.1186/1471-2164-15-102);
[database](http://webapps.bifi.es/prionscan).
13. SAPdb:
[publication](https://doi.org/https://doi.org/10.1016/j.compbiomed.2021.104391);
[publication](https://doi.org/10.1016/j.compbiomed.2021.104391);
[database](https://webs.iiitd.edu.in/raghava/sapdb/).
14. StAmP:
[publication](https://doi.org/https://doi.org/10.1093/bioinformatics/btac126);
[publication](https://doi.org/10.1093/bioinformatics/btac126);
[database](https://stamp.switchlab.org/).
15. Waltz DB 2.0:
[publication](https://doi.org/https://doi.org/10.1093/nar/gkz758);
15. Waltz DB 2.0: [publication](https://doi.org/10.1093/nar/gkz758);
[database](http://waltzdb.switchlab.org/).

## Non-active

1. AmyCo:
[publication](https://doi.org/https://doi.org/10.1080/13506129.2019.1603143);
1. AmyCo: [publication](https://doi.org/10.1080/13506129.2019.1603143);
[database](http://bioinformatics.biol.uoa.gr/amyco).
2. amyloid interactome:
[publication](https://doi.org/https://doi.org/10.1371/journal.pone.0173163);
[publication](https://doi.org/10.1371/journal.pone.0173163);
[database](http://83.212.109.111/amyloid_interactome).
3. Amyloïdose gezamenlijk:
[publication](https://doi.org/https://doi.org/10.3109/13506129.2014.964858);
[publication](https://doi.org/10.3109/13506129.2014.964858);
[database](http://www.amyloidosis.nl/).
4. AmyPDB:
[publication](https://doi.org/https://doi.org/10.1186/1471-2105-9-273);
4. AmyPDB: [publication](https://doi.org/10.1186/1471-2105-9-273);
[database](http://amypdb.genouest.org/;%20https://amypdb.univ-rennes1.fr/).
5. fibril_one:
[publication](https://doi.org/https://doi.org/10.1110%2Fps.0204302);
5. fibril_one: [publication](https://doi.org/10.1110%2Fps.0204302);
[database](http://www.bioinformatics.leeds.ac.uk/group/online/fibril_one).
6. pE-DB:
[publication](https://doi.org/https://doi.org/10.1093/nar/gkt960);
6. pE-DB: [publication](https://doi.org/10.1093/nar/gkt960);
[database](https://pedb.vib.be/).
7. PrionHome:
[publication](https://doi.org/https://doi.org/10.1371/journal.pone.0031785);
[publication](https://doi.org/10.1371/journal.pone.0031785);
[database](https://libaio.biol.mcgill.ca/prion).
8. ProADD:
[publication](https://doi.org/https://doi.org/10.6026%2F97320630010390);
8. ProADD: [publication](https://doi.org/10.6026%2F97320630010390);
[database](http://bicmku.in/ProADD).
9. The Prion Disease Database:
[publication](https://doi.org/https://doi.org/10.1093/database/bap011);
[publication](https://doi.org/10.1093/database/bap011);
[database](http://prion.systemsbiology.net).
10. THERPA v2:
[publication](https://doi.org/http://dx.doi.org/10.1080/19336896.2019.1689789);
[publication](http://dx.doi.org/10.1080/19336896.2019.1689789);
[database](http://www.nih.go.kr/therpa%20;%20https://therpa.pythonanywhere.com/).
11. ZipperDB:
[publication](https://doi.org/https://doi.org/10.1073/pnas.0915166107);
11. ZipperDB: [publication](https://doi.org/10.1073/pnas.0915166107);
[database](https://services.mbi.ucla.edu/zipperdb/intro).

### About and citation
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1 change: 1 addition & 0 deletions docs/index.Rmd
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library(DT)
library(dplyr)
library(stringr)
dat <- readr::read_csv("../data/amyloid_db.csv", col_select = c(, 1:14), col_types = "fcfffffff?cccf") %>%
# filter(`Current status` == "Active") %>%
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