Improved prediction and characterization of anticancer activities of peptides using a novel flexible scoring card method

Amino acids in cancer

(2020) Elizabeth L. Lieu et al.   EXPERIMENTAL AND MOLECULAR MEDICINE

Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening

(2020) Shaherin Basith et al.   MEDICINAL RESEARCH REVIEWS

PVPred-SCM: Improved Prediction and Analysis of Phage Virion Proteins Using a Scoring Card Method

(2020) Phasit Charoenkwan et al.   Cells

HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation

(2020) Md Mehedi Hasan et al.   BIOINFORMATICS

PPTPP: A novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning

(2020) Yu P Zhang et al.   BIOINFORMATICS

Dietary restriction of amino acids for Cancer therapy

(2020) Jian-Sheng Kang   Nutrition & Metabolism

iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides

(2020) Phasit Charoenkwan et al.   GENOMICS

Anticancer peptide: Physicochemical property, functional aspect and trend in clinical application (Review)

(2020) Wararat Chiangjong et al.   INTERNATIONAL JOURNAL OF ONCOLOGY

iUmami-SCM: A Novel Sequence-Based Predictor for Prediction and Analysis of Umami Peptides Using a Scoring Card Method with Propensity Scores of Dipeptides

(2020) Phasit Charoenkwan et al.   Journal of Chemical Information and Modeling

ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations

(2020) Mst. Shamima Khatun et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

iDPPIV-SCM: A Sequence-Based Predictor for Identifying and Analyzing Dipeptidyl Peptidase IV (DPP-IV) Inhibitory Peptides Using a Scoring Card Method

(2020) Phasit Charoenkwan et al.   JOURNAL OF PROTEOME RESEARCH

iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features

(2020) Md. Mehedi Hasan et al.   GENOMICS PROTEOMICS & BIOINFORMATICS

DBS: a fast and informative segmentation algorithm for DNA copy number analysis

(2019) Jun Ruan et al.   BMC BIOINFORMATICS

Oxidative Stress and Cancer

(2019) James E. Klaunig   CURRENT PHARMACEUTICAL DESIGN

PEPred-Suite: improved and robust prediction of therapeutic peptides using adaptive feature representation learning

(2019) Leyi Wei et al.   BIOINFORMATICS

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

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

Cationic block amphiphiles show anti-mitochondrial activity in multi-drug resistant breast cancer cells

(2019) Petro P. Czupiel et al.   JOURNAL OF CONTROLLED RELEASE

ACPred: A Computational Tool for the Prediction and Analysis of Anticancer Peptides

(2019) Nalini Schaduangrat et al.   MOLECULES

ACP-DL: A Deep Learning Long Short-Term Memory Model to Predict Anticancer Peptides Using High Efficiency Feature Representation

(2019) Hai-Cheng Yi et al.   Molecular Therapy-Nucleic Acids

The Diverse Functions of Non-Essential Amino Acids in Cancer

(2019) Bo-Hyun Choi et al.   Cancers

TargetAntiAngio: A Sequence-Based Tool for the Prediction and Analysis of Anti-Angiogenic Peptides

(2019) Vishuda Laengsri et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

ACPred-Fuse: fusing multi-view information improves the prediction of anticancer peptides

(2019) Bing Rao et al.   BRIEFINGS IN BIOINFORMATICS

Antioxidant Peptides from Terrestrial and Aquatic Plants Against Cancer

(2018) Enrique Marquez-Rios et al.   CURRENT PROTEIN & PEPTIDE SCIENCE

A Novel Hybrid Sequence-Based Model for Identifying Anticancer Peptides

(2018) Lei Xu et al.   Genes

Intelligent computational method for discrimination of anticancer peptides by incorporating sequential and evolutionary profiles information

(2018) Muhammad Kabir et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

PAAP: a web server for predicting antihypertensive activity of peptides

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

Molecular insights of newly identified potential peptide inhibitors of hypoxia inducible factor 1α causing breast cancer

(2018) Dharmar Manimaran et al.   JOURNAL OF MOLECULAR STRUCTURE

HemoPred: a web server for predicting the hemolytic activity of peptides

(2017) Thet Su Win et al.   Future Medicinal Chemistry

Antioxidative Categorization of Twenty Amino Acids Based on Experimental Evaluation

(2017) Naijin Xu et al.   MOLECULES

MLACP: machine-learning-based prediction of anticancer peptides

(2017) Balachandran Manavalan et al.   Oncotarget

Surface Physical Activity and Hydrophobicity of Designed Helical Peptide Amphiphiles Control Their Bioactivity and Cell Selectivity

(2016) Cuixia Chen et al.   ACS Applied Materials & Interfaces

iACP: a sequence-based tool for identifying anticancer peptides

(2016) Wei Chen et al.   Oncotarget

Identifying anticancer peptides by using improved hybrid compositions

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

Highly Cytotoxic Bioconjugated Gold(I) Complexes with Cysteine-Containing Dipeptides

(2015) Alejandro Gutiérrez et al.   CHEMISTRY-A EUROPEAN JOURNAL

AntiAngioPred: A Server for Prediction of Anti-Angiogenic Peptides

(2015) Azhagiya Singam Ettayapuram Ramaprasad et al.   PLoS One

Amino acid management in cancer

(2015) Zhi-Yang Tsun et al.   SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY

New peptide architectures through C–H activation stapling between tryptophan–phenylalanine/tyrosine residues

(2015) Lorena Mendive-Tapia et al.   Nature Communications

ACPP: A Web Server for Prediction and Design of Anti-cancer Peptides

(2014) Saravanan Vijayakumar et al.   International Journal of Peptide Research and Therapeutics

Design of potent, non-toxic anticancer peptides based on the structure of the antimicrobial peptide, temporin-1CEa

(2013) Qing-Zhu Yang et al.   ARCHIVES OF PHARMACAL RESEARCH

Molecular mechanisms of anticancer action and cell selectivity of short α-helical peptides

(2013) Cuixia Chen et al.   BIOMATERIALS

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 approaches for designing highly effective cell penetrating peptides

(2013) Ankur Gautam et al.   Journal of Translational Medicine

SCMCRYS: Predicting Protein Crystallization Using an Ensemble Scoring Card Method with Estimating Propensity Scores of P-Collocated Amino Acid Pairs

(2013) Phasit Charoenkwan et al.   PLoS One

In Silico Approach for Predicting Toxicity of Peptides and Proteins

(2013) Sudheer Gupta et al.   PLoS One

In Silico Models for Designing and Discovering Novel Anticancer Peptides

(2013) Atul Tyagi et al.   Scientific Reports

Designed Antimicrobial and Antitumor Peptides with High Selectivity

(2011) Jing Hu et al.   BIOMACROMOLECULES

Studies on Mechanism of Action of Anticancer Peptides by Modulation of Hydrophobicity Within a Defined Structural Framework

(2011) Y.-b. Huang et al.   MOLECULAR CANCER THERAPEUTICS

Serum Stabilities of Short Tryptophan- and Arginine-Rich Antimicrobial Peptide Analogs

(2010) Leonard T. Nguyen et al.   PLoS One