PTPD: predicting therapeutic peptides by deep learning and word2vec

mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides

(2019) Vinothini Boopathi et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

A Novel Hybrid Sequence-Based Model for Identifying Anticancer Peptides

(2018) Lei Xu et al.   Genes

PAAP: a web server for predicting antihypertensive activity of peptides

(2018) Thet Su Win et al.   Future Medicinal Chemistry

PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions

(2018) Balachandran Manavalan et al.   Frontiers in Immunology

mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation

(2018) Balachandran Manavalan et al.   BIOINFORMATICS

Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools

(2018) Ran Su et al.   BRIEFINGS IN BIOINFORMATICS

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

(2017) Shaoqing Ren et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Computational prediction of therapeutic peptides based on graph index

(2017) Chunrui Xu et al.   JOURNAL OF BIOMEDICAL INFORMATICS

G-MS2F: GoogLeNet based multi-stage feature fusion of deep CNN for scene recognition

(2017) Pengjie Tang et al.   NEUROCOMPUTING

MLACP: machine-learning-based prediction of anticancer peptides

(2017) Balachandran Manavalan et al.   Oncotarget

Region-Based Convolutional Networks for Accurate Object Detection and Segmentation

(2016) Ross Girshick et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

An expanded sequence context model broadly explains variability in polymorphism levels across the human genome

(2016) Varun Aggarwala et al.   NATURE GENETICS

A novel word embedding learning model using the dissociation between nouns and verbs

(2016) Baotian Hu et al.   NEUROCOMPUTING

Identifying anticancer peptides by using improved hybrid compositions

(2016) Feng-Min Li et al.   Scientific Reports

Global cancer statistics, 2012

(2015) Lindsey A. Torre et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Chinese comments sentiment classification based on word2vec and SVMperf

(2015) Dongwen Zhang et al.   EXPERT SYSTEMS WITH APPLICATIONS

Alpha-Helical Cationic Anticancer Peptides: A Promising Candidate for Novel Anticancer Drugs

(2015) Yibing Huang et al.   MINI-REVIEWS IN MEDICINAL CHEMISTRY

An Empirical Study of Different Approaches for Protein Classification

(2014) Loris Nanni et al.   TheScientificWorldJOURNAL

Predicting anticancer peptides with Chou′s pseudo amino acid composition and investigating their mutagenicity via Ames test

(2013) Zohre Hajisharifi et al.   JOURNAL OF THEORETICAL BIOLOGY

In Silico Models for Designing and Discovering Novel Anticancer Peptides

(2013) Atul Tyagi et al.   Scientific Reports

DADP: the database of anuran defense peptides

(2012) Mario Novković et al.   BIOINFORMATICS

Identifying Bacterial Virulent Proteins by Fusing a Set of Classifiers Based on Variants of Chou's Pseudo Amino Acid Composition and on Evolutionary Information

(2011) Loris Nanni et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Oncolytic Activities of Host Defense Peptides

(2011) Sammy Al-Benna et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

How to apply de Bruijn graphs to genome assembly

(2011) Phillip E C Compeau et al.   NATURE BIOTECHNOLOGY

VirulentPred: a SVM based prediction method for virulent proteins in bacterial pathogens

(2008) Aarti Garg et al.   BMC BIOINFORMATICS

An ensemble of support vector machines for predicting virulent proteins

(2008) Loris Nanni et al.   EXPERT SYSTEMS WITH APPLICATIONS