Simple Stochastic Fingerprints Towards Mathematical Modeling in Biology and Medicine 2. Unifying Markov Model for Drugs Side Effects-Reference-Cited by-同舟云学术

Simple Stochastic Fingerprints Towards Mathematical Modeling in Biology and Medicine 2. Unifying Markov Model for Drugs Side Effects

Published:2006-07-18 Issue:7 Volume:68 Page:1527-1554
ISSN:0092-8240
Container-title:Bulletin of Mathematical Biology
language:en
Short-container-title:Bull. Math. Biol.

Author:

Cruz-Monteagudo Maykel,González-Díaz Humberto,Uriarte Eugenio

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,General Agricultural and Biological Sciences,Pharmacology,General Environmental Science,General Biochemistry, Genetics and Molecular Biology,General Mathematics,Immunology,General Neuroscience

Link

http://link.springer.com/content/pdf/10.1007/s11538-005-9013-4.pdf

Reference61 articles.

1. Briggs, J.M., Marrone, T.J., McCammon, J.A., 1996. Computational science new horizons and relevance to pharmaceutical design. Trends Cardiovasc. Med. 6, 198–203.

2. Cabrera, M.A., González, D.H., Teruel, C., Pla-Delfina, J.M., Bermejo del Val, M., 2002. A novel approach to determining physicochemical and absorption properties of 6-fluoroquinolone derivatives: experimental assessment. Eur. J. Pharm. Biopharm. 53, 317–325.

3. Cabrera, M.A., Bermejo, S., 2004. In silico prediction of central nervous system activity of compounds. Identification of potential pharmacophores by the TOPS–MODE approach. Bioorg. Med. Chem. 22, 5833–5843.

4. Chou, K.-C., 1993. A vectorized sequence-coupling model for predicting HIV protease cleavage sites in proteins. J. Biol. Chem. 268, 16938–16948.

5. Chou, K.C., 1997. Prediction and classification of -turn types. Biopolymers 42, 837.

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Drug Side-effect Profiles Prediction: From Empirical Risk Minimization to Structural Risk Minimization;IEEE/ACM Transactions on Computational Biology and Bioinformatics;2018

2. In silico assessment of adverse drug reactions and associated mechanisms;Drug Discovery Today;2016-01

3. ARWAR: A network approach for predicting Adverse Drug Reactions;Computers in Biology and Medicine;2016-01

4. A new approach to identify, classify and count drug-related events;British Journal of Clinical Pharmacology;2013-09

5. From QSAR models of Drugs to Complex Networks: State-of-Art Review and Introduction of New Markov-Spectral Moments Indices;Current Topics in Medicinal Chemistry;2012-03-01