Bacterial infections caused by 'superbugs' are increasing globally, and conventional
antibiotics are becoming less effective against these bacteria, such that we risk entering a …

Antimicrobial peptides (AMPs) are distributed across all kingdoms of life and are an
indispensable component of host defenses. They consist of predominantly short cationic …

Neuromorphic computing, a computing paradigm inspired by the human brain, enables
energy-efficient and fast artificial neural networks. To process information, neuromorphic …

Systematically identifying functional peptides is difficult owing to the vast combinatorial
space of peptide sequences. Here we report a machine-learning pipeline that mines the …

The increased incidence of bacterial resistance to available antibiotics represents a major
global health problem and highlights the need for novel anti-infective therapies …

The antimicrobial peptide database (APD, http://aps. unmc. edu/AP/) is an original database
initially online in 2003. The APD2 (2009 version) has been regularly updated and further …

Cancer is a Toxic health concern worldwide, it happens when cellular modifications cause
the irregular growth and division of human cells. Several traditional approaches such as …

Discovery and development of biopeptides are time‐consuming, laborious, and dependent
on various factors. Data‐driven computational methods, especially machine learning (ML) …

Abstract CancerPPD (http://crdd. osdd. net/raghava/cancerppd/) is a repository of
experimentally verified anticancer peptides (ACPs) and anticancer proteins. Data were …

We present a generative long short-term memory (LSTM) recurrent neural network (RNN) for
combinatorial de novo peptide design. RNN models capture patterns in sequential data and …