ToxinPred 3.0: An improved method for predicting the toxicity of peptides
Toxicity emerges as a prominent challenge in the design of therapeutic peptides, causing
the failure of numerous peptides during clinical trials. In 2013, our group developed …
the failure of numerous peptides during clinical trials. In 2013, our group developed …
Prediction of antiviral peptides using transform evolutionary & SHAP analysis based descriptors by incorporation with ensemble learning strategy
Viral diseases are a major health concern in the last few years. Antiviral peptides (AVPs)
belong to a type of antimicrobial peptides (AMPs) that have the high potential to defend the …
belong to a type of antimicrobial peptides (AMPs) that have the high potential to defend the …
Signal peptide efficiency: from high-throughput data to prediction and explanation
S Grasso, V Dabene, MMWB Hendriks… - ACS synthetic …, 2023 - ACS Publications
The passage of proteins across biological membranes via the general secretory (Sec)
pathway is a universally conserved process with critical functions in cell physiology and …
pathway is a universally conserved process with critical functions in cell physiology and …
Advancing Peptide-Based Cancer Therapy with AI: In-Depth Analysis of State-of-the-Art AI Models
Anticancer peptides (ACPs) play a vital role in selectively targeting and eliminating cancer
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …
Accelerating the discovery of anticancer peptides through deep forest architecture with deep graphical representation
Cancer is one of the leading diseases threatening human life and health worldwide. Peptide-
based therapies have attracted much attention in recent years. Therefore, the precise …
based therapies have attracted much attention in recent years. Therefore, the precise …
PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation
Anticancer peptides (ACPs) perform a promising role in discovering anti-cancer drugs. The
growing research on ACPs as therapeutic agent is increasing due to its minimal side effects …
growing research on ACPs as therapeutic agent is increasing due to its minimal side effects …
LBCEPred: a machine learning model to predict linear B-cell epitopes
B-cell epitopes have the capability to recognize and attach to the surface of antigen
receptors to stimulate the immune system against pathogens. Identification of B-cell epitopes …
receptors to stimulate the immune system against pathogens. Identification of B-cell epitopes …
[HTML][HTML] StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features
Host defense or antimicrobial peptides (AMPs) are promising candidates for protecting host
against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type …
against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type …
Applications of peptide-based nanomaterials in targeting cancer therapy
B Sun, L Zhang, M Li, X Wang, W Wang - Biomaterials Science, 2024 - pubs.rsc.org
To meet the demand for precision medicine, researchers are committed to develo** novel
strategies to reduce systemic toxicity and side effects in cancer treatment. Targeting peptides …
strategies to reduce systemic toxicity and side effects in cancer treatment. Targeting peptides …
ME-ACP: multi-view neural networks with ensemble model for identification of anticancer peptides
Cancer remains one of the most threatening diseases, which kills millions of lives every
year. As a promising perspective for cancer treatments, anticancer peptides (ACPs) …
year. As a promising perspective for cancer treatments, anticancer peptides (ACPs) …