Showing posts with label machine learning. Show all posts
Showing posts with label machine learning. Show all posts
Thursday, February 23, 2012
Tuesday, January 25, 2011
WORKSHOP- COMPUTATIONAL APPROACHES IN BIOLOGICAL DATA MINING
A Workshop on Computational Approaches in Biological Data mining is being organised by the
Unit Of Simulation and Informatics, Indian Agricultural Research Institute, New Delhi.
The topics to be discussed are:-
Application deadline:- February 25th, 2011.
Do you wish to know more?
- Introduction to Biological databases
- Biological data mining
- Concept and application of machine learning techniques in bioinformatics
- Tools and techniques for bio-molecular prediction
- Future directions in biological data mining.
Application deadline:- February 25th, 2011.
Do you wish to know more?
Friday, August 13, 2010
Protein Structure and Drug Discovery Workshop
"Protein Structure and Drug Discovery" Workshop – Sept 30th to Oct 1st 2010 La Jolla, CA.
Please join us at MolSoft's ( www.molsoft.com ) "Protein Structure and Drug Design" Workshop in La Jolla, California USA. For more information and a registration form see: www.molsoft.com/training.html
This workshop is suitable for chemists and biologists who would like to learn more about computational drug discovery and bioinformatics. No prior knowledge in this field is required to participate. The workshop is presented by Prof. Ruben Abagyan (University of California San Diego) and Dr. Maxim Totrov (MolSoft).
Price: $349 (Academics) $749 (Commercial)
The workshops will consist of lectures, demonstrations, and "hands-on" computational experiments and will cover the following topics:
- How To Display Fully Interactive 3D Molecules in PowerPoint and the Web
- Sequence and Protein Structure Analysis
- Protein Modeling and Simulations
- Structure Validation and Optimization
- Ligand Binding Site Prediction
- Small Molecule Docking and Virtual Ligand Screening
- Structure-based development of target-specific compound libraries
- Cheminformatics, Chemical Clustering, Searching, Superposition etc...
- QSAR, Machine Learning
- Protein-Protein Docking
Please see our website at www.molsoft.com for more details or E mail: andy@molsoft.com or call 858-625-2000 ext.108. For the latest MolSoft news see: http://www.molsoft.com/news.
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Please join us at MolSoft's ( www.molsoft.com ) "Protein Structure and Drug Design" Workshop in La Jolla, California USA. For more information and a registration form see: www.molsoft.com/training.html
This workshop is suitable for chemists and biologists who would like to learn more about computational drug discovery and bioinformatics. No prior knowledge in this field is required to participate. The workshop is presented by Prof. Ruben Abagyan (University of California San Diego) and Dr. Maxim Totrov (MolSoft).
Price: $349 (Academics) $749 (Commercial)
The workshops will consist of lectures, demonstrations, and "hands-on" computational experiments and will cover the following topics:
- How To Display Fully Interactive 3D Molecules in PowerPoint and the Web
- Sequence and Protein Structure Analysis
- Protein Modeling and Simulations
- Structure Validation and Optimization
- Ligand Binding Site Prediction
- Small Molecule Docking and Virtual Ligand Screening
- Structure-based development of target-specific compound libraries
- Cheminformatics, Chemical Clustering, Searching, Superposition etc...
- QSAR, Machine Learning
- Protein-Protein Docking
Please see our website at www.molsoft.com for more details or E mail: andy@molsoft.com or call 858-625-2000 ext.108. For the latest MolSoft news see: http://www.molsoft.com/news.
Share |
Thursday, May 8, 2008
Computational intelligence approaches for pattern discovery in biological systems
Natural Selection, Inc. is a very interesting find that i came across after reading through a publication in Oxford journals. This company has unique expertise in computational intelligence applied to bioinformatics problems. Led by Dr. Gary Fogel. The bioinformatics team there has developed a suite of computational tools for small molecule lead discovery and optimization.
Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.
Do you want to know more?
Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.
Do you want to know more?
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