ArticleBioinformation2019
BioDADPep: A Bioinformatics database for anti diabetic peptides.
Article in Bioinformation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- BertADP: a fine-tuned protein language model for anti-diabetic peptide prediction.BMC biology · 2025Article
- A comprehensive dataset of therapeutic peptides on multi-function property and structure information.Scientific data · 2025Article
- Predicting Antidiabetic Peptide Activity: A Machine Learning Perspective on Type 1 and Type 2 Diabetes.International journal of molecular sciences · 2024Article
- In Silico Prospecting for Novel Bioactive Peptides from Seafoods: A Case Study on Pacific Oyster (Molecules (Basel, Switzerland) · 2023Article
- MFPPDB: a comprehensive multi-functional plant peptide database.Frontiers in plant science · 2023Article
- PhytoSelectDBT: A database for the molecular models of anti-diabetic targets docked with bioactive peptides from selected ethno-medicinal plants.Bioinformation · 2023Article
- PrMFTP: Multi-functional therapeutic peptides prediction based on multi-head self-attention mechanism and class weight optimization.PLoS computational biology · 2022Article
- MPMABP: A CNN and Bi-LSTM-Based Method for Predicting Multi-Activities of Bioactive Peptides.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Article
- MultiPep: a hierarchical deep learning approach for multi-label classification of peptide bioactivities.Biology methods & protocols · 2021Article
- Therapeutic peptides and their delivery using lipid-based nanoparticles.Tzu chi medical journalReview
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing number of cases for diabetes worldwide is a concern. Therefore, it is of interest to design therapeutic peptides to overcome side effects caused by the available drugs. It should be noted that data on several known anti-diabetic peptides is available in the literature in an organized manner. Hence, it is of interest to collect, glean and store such data in form of a searchable database supported by RDBMS. Data on anti-diabetic peptides and their related data are collected from the literature using manual search. Data on related peptides from other databases (THPdb, ADP3, LAMP, AHTPDB, AVPdb, BioPepDB, CancerPPD, CPPsite, DRAMP, SATPdb, CAMPR3 and MBPDB) are also included after adequate curation. Thus, we describe the development and utility of BioDADPep, a Bioinformatics database for anti-diabetic peptides. The database has cross-reference for antidiabetic peptides. The database is enabled with a web-based GUI using a simple Google-like search function. Data presented in BioDADPep finds application in the design of an effective anti-diabetic peptide.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.