chemistry

Molecule mining

Molecule mining is a chemistry topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Molecule mining rather than just read about it. In short: Molecule mining is the process of data mining, or extracting and discovering patterns, as applied to molecules. Since molecules may be represented by molecular graphs, this is strongly related to graph mining and structured data mining.

Key takeaways

Molecule mining belongs to chemistry; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Molecule mining to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Molecule mining from memory before moving on to harder problems.

Reference excerpt

Molecule mining is the process of data mining, or extracting and discovering patterns, as applied to molecules. Since molecules may be represented by molecular graphs, this is strongly related to graph mining and structured data mining. The main problem is how to represent molecules while discriminating the data instances. One way to do this is chemical similarity metrics, which has a long tradition in the field of cheminformatics. Typical approaches to calculate chemical similarities use chemical fingerprints, but this loses the underlying information about the molecule topology. Mining the molecular graphs directly avoids this problem. So does the inverse QSAR problem which is preferable for vectorial mappings.

Coding(Moleculei,Moleculej≠i)

Kernel methods Marginalized graph kernel Optimal assignment kernel Pharmacophore kernel C++ (and R) implementation combining the marginalized graph kernel between labeled graphs extensions of the marginalized kernel Tanimoto kernels graph kernels based on tree patterns kernels based on pharmacophores for 3D structure of molecules

Maximum common graph methods MCS-HSCS (Highest Scoring Common Substructure (HSCS) ranking strategy for single MCS) Small Molecule Subgraph Detector (SMSD)- is a Java-based software library for calculating Maximum Common Subgraph (MCS) between small molecules. This will help us to find similarity/distance between two molecules. MCS is also used for screening drug like compounds by hitting molecules, which share common subgraph (substructure).

Coding(Moleculei)

Molecular query methods Warmr AGM PolyFARM FSG MolFea MoFa/MoSS Gaston LAZAR ParMol (contains MoFa, FFSM, gSpan, and Gaston) optimized gSpan SMIREP DMax SAm/AIm/RHC AFGen gRed G-Hash

Methods based on special architectures of neural networks BPZ ChemNet CCS MolNet Graph machines

See also Molecular Query Language Chemical graph theory Chemical space QSAR ADME partition coefficient

References

Further reading Schölkopf, B., K. Tsuda and J. P. Vert: Kernel Methods in Computational Biology, MIT Press, Cambridge, MA, 2004. R.O. Duda, P.E. Hart, D.G. Stork, Pattern Classification, John Wiley & Sons, 2001. ISBN 0-471-05669-3 Gusfield, D., Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology, Cambridge University Press, 1997. ISBN 0-521-58519-8 R. Todeschini, V. Consonni, Handbook of Molecular Descriptors, Wiley-VCH, 2000. ISBN 3-527-29913-0

External links Small Molecule Subgraph Detector (SMSD) - is a Java-based software library for calculating Maximum Common Subgraph (MCS) between small molecules. 5th International Workshop on Mining and Learning with Graphs, 2007 Overview for 2006 Molecule mining (basic chemical expert systems) ParMol and master thesis documentation - Java - Open source - Distributed mining - Benchmark algorithm library Technical University of Munich (TUM) - Kramer group Molecule mining (advanced chemical expert systems) DMax Chemistry Assistant - commercial software AFGen - Software for generating fragment-based descriptors

Worked examples

Example 1 — a first encounter with Molecule mining

Start with the simplest possible case. Write down what Molecule mining claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In chemistry, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Molecule mining before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Molecule mining ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Molecule mining

In research: Molecule mining appears in chemistry research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Molecule mining in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Molecule mining is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cheminformatics, Computational chemistry, Data mining, so understanding it makes those chapters shorter.
In everyday life: Look for Molecule mining outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Molecule mining in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Molecule mining means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Molecule mining out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Molecule mining in simple terms?

Why does Molecule mining matter?

Because it connects several chemistry ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Molecule mining?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Molecule mining.