UGM 2007 Training

ChemAxon 0815c054e1

21-06-2007 10:39:11

Archive of all tasks and demos of the Training day

ChemAxon 0815c054e1

28-06-2007 16:14:40

Structural Search

Trainer: Szabolcs Csepregi


1. Searching in the JSP application, exploring thin client architecture

2. Searching in IJC

3. Search features

4. Search options

5. Reaction search

Training demo:


Structural Search Using ChemAxon Tools (.ppt) (poster format in pdf)

JChem Query guide

JChem Base web application (JSP) examples:

ChemAxon e08c317633

02-07-2007 12:47:07

Chemical Terms

Trainer: Zsolt Mohácsi


1. Property calculations with Chemical Terms

2. Elements of the Chemical Terms language

3. Filtering with Chemical Terms

4. Match functions in Chemical Terms

Training demo:

(Remaining videos are coming soon.)


Chemical Terms, a Language for Cheminformatics (.ppt)

Chemical Term Language Reference

Chemical Terms Reference Tables

Predefined Molecules and Molecule Sets

ChemAxon 0815c054e1

04-07-2007 11:22:40

Reactor Training

Trainer: Gyorgy Pirok


1. Combinatorial enumeration

Generate a reaction library

2. Reaction Design

Design a reaction and test it with added examples in the Reaction Editor and in the Reaction Wizard




ChemAxon 0815c054e1

04-07-2007 11:43:57

Instant JChem Training

Trainer: Tim Dudgeon


1. Open the demo data

2. Explore the PubChem demo data

3. Explore the Wombat data

4. Import 'result2.smiles' into IJC

5. Import 'result4.smiles' into IJC

6. Import 'result1.smiles' into IJC

7. Use the 'Schema Editor' to view the database contents

8. Import 'screening_collection.sdf'

9. Build a form

10. Query your data

11. Apply a Standardizer

Training demo:


Standardizer license is needed to specify non-default standardization in the last exercise

ChemAxon 0815c054e1

04-07-2007 12:43:43

LibMCS Training

Trainer: Miklos Vargyas


Maximum Common Substructure clustering of structure sets with Library MCS: Identify diverse sets through; import structure sets and related data into LibraryMCS, fast clustering for initial evaluation, tune parameters to explore clustering outcomes, perform exhaustive clustering with 'best' parameters, select novel scaffolds.