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PatternHunter

PatternHunter is a computer science 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 PatternHunter rather than just read about it. In short: PatternHunter is a commercially available homology search instrument software that uses sequence alignment techniques. It was initially developed in the year 2002 by three scientists: Bin Ma, John Tramp and Ming Li.

Key takeaways

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

Reference excerpt

PatternHunter is a commercially available homology search instrument software that uses sequence alignment techniques. It was initially developed in the year 2002 by three scientists: Bin Ma, John Tramp and Ming Li. These scientists were driven by the desire to solve the problem that many investigators face during studies that involve genomics and proteomics. These scientists realized that such studies greatly relied on homology studies that established short seed matches that were subsequently lengthened. Describing homologous genes was an essential part of most evolutionary studies and was crucial to the understanding of the evolution of gene families, the relationship between domains and families. Homologous genes could only be studied effectively using search tools that established like portions or local placement between two proteins or nucleic acid sequences. Homology was quantified by scores obtained from matching sequences, “mismatch and gap scores”.

Development In comparative genomics, for example, it is necessary to compare huge chromosomes such as those found in the human genome. However, the immense expansion of genomic data introduces a predicament in the available methods of carrying out homology searches. For instance, enlarging the seed size lowers sensitivity while reducing seed size reduces the speed of calculations. Several sequence alignment programs have been developed to determine homology between genes. These include FASTA, the BLAST family, QUASAR, MUMmer, SENSEI, SIM, and REPuter. They mostly use Smith-Waterman alignment technique, which compares bases against other bases, but is too slow. BLAST makes an improvement to this technique by establishing brief, precise seed matches that it later joins up to form longer alignments. However, when dealing with lengthy sequences, the above-mentioned techniques are extremely sluggish and required considerable memory sizes. SENSEI, however, is more efficient than the other methods, but is incompetent in other forms of alignment as its strength lies in handling ungapped alignments. The quality of the production from Megablast, on the other hand, is of poor quality and does not adapt well to large sequences. Techniques such as MUMmer and QUASAR employ suffix trees, which are supposed to handle exact matches. However, these methods can only apply to the comparison of sequences that display elevated similarities. All the above-mentioned problems necessitate the development of a fast reliable tool that can handle all types of sequences efficiently without consuming too many resources in a computer.

Approach PatternHunter utilizes numerous seeds (tiny search strings) with optimal intervals between them. Searches that employ seeds are extremely fast because they only determine homology in places where hits are established. The sensitivity of a search string is greatly influenced by the amount of space between adjacent strings. Large seeds are unable to find isolated homologies, whereas small ones generate numerous arbitrary hits that delay computation. PatternHunter strikes a delicate balance in this area by providing optimal spacing between search strings. It uses alternate k (k = 11) letters as seeds in contrast with BLAST, which utilizes successive k letters as seeds. The first stage in PatternHunter analysis entails a filtering phase where the program hunts for matches in k alternating points as denoted by the most advantageous pattern. The second stage is the alignment phase, which is identical to BLAST. In addition, it is possible to use more than one seed at a go with PatternHunter. This elevates the sensitivity of the tool without interfering with its speed.

Speed PatternHunter takes a short time to analyze all types of sequences. On a modern computer, it can take a few seconds to handle prokaryotic genomes, minutes to process Arabidopsis thaliana sequences and several hours to process a human chromosome. When compared to other tools, PatternHunter exhibits speeds that are approximately a hundred times faster than BLAST and Mega BLAST. These speeds are 3000-fold those attained from a Smith-Waterman algorithm. In addition, the program has a user-friendly interface that allows one to customize the search parameters.

Sensitivity In terms of sensitivity, it is possible to attain the optimum sensitivity with PatternHunter while still retaining the same speed as a conventional BLAST search.

Specifications The designing of PatternHunter uses Java technology. Consequently, the program runs smoothly when installed in any Java 1.4 environments.

Future advances Homology search is a very lengthy procedure that requires a lot of time. Challenges still remain in handling DNA-DNA searches as well as translated DNA-protein searches because of the vast sizes of databases and the tiny query that is used. PatternHunter has been improved to an upgraded PatternHunter II version, which hastens DNA-protein searches a hundredfold without altering the sensitivity. However, there are plans to improve PatternHunter to attain the high sensitivity of the Smith - Waterman tool while obtaining BLAST pace. A novel translated PatternHunter that intends to hasten tBLASTx. is also in the developmental stages.

References

Worked examples

Example 1 — a first encounter with PatternHunter

Start with the simplest possible case. Write down what PatternHunter claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, 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 PatternHunter 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 PatternHunter 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 PatternHunter

In research
PatternHunter appears in computer science 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 PatternHunter 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
PatternHunter is common in secondary-school and first-year university syllabi. It links to neighbouring topics Bioinformatics software, so understanding it makes those chapters shorter.
In everyday life
Look for PatternHunter 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 PatternHunter in 20 minutes

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

Frequently asked questions

What is PatternHunter in simple terms?

PatternHunter is a commercially available homology search instrument software that uses sequence alignment techniques. It was initially developed in the year 2002 by three scientists: Bin Ma, John Tramp and Ming Li.

Why does PatternHunter matter?

Because it connects several computer science 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 PatternHunter?

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 PatternHunter.

Tags

  • Bioinformatics software

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