Bioinformatics Programming Using Python: Practical by Mitchell L. Model

By Mitchell L. Model

Powerful, versatile, and simple to exploit, Python is a perfect language for development software program instruments and functions for all times technology examine and improvement. This special ebook exhibits you the way to software with Python, utilizing code examples taken at once from bioinformatics. very quickly, you'll be utilizing refined concepts and Python modules which are relatively potent for bioinformatics programming.

Bioinformatics Programming utilizing Python is ideal for a person concerned with bioinformatics -- researchers, aid employees, scholars, and software program builders attracted to writing bioinformatics purposes. You'll locate it beneficial no matter if you already use Python, write code in one other language, or haven't any programming event in any respect. It's an outstanding self-instruction software, in addition to a convenient reference while dealing with the demanding situations of real-life programming tasks.
* get to grips with Python's basics, together with how one can boost easy functions
* how to use Python modules for development matching, dependent textual content processing, on-line info retrieval, and database entry
* realize generalized styles that disguise a wide percentage of ways Python code is utilized in bioinformatics
* how to practice the foundations and methods of object-oriented programming
* enjoy the "tips and traps" part in every one chapter

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Everything inside a pair of parentheses will be evaluated completely before the result is used in another operation. For instance, parentheses could be used as follows to make the result of the preceding example be 17: >>> (4 + 2) * 3 − 1 17 Comparisons can be combined to form “between” expressions: >>> 1 < 4 < 6 True >>> 2 <= 2 < 5 True >>> 2 < 2 < 5 False Strings can participate in sequences of operations: >>> 'tc' in ('ttt' + 'ccc' + 'ggg' + 'aaa') True >>> 'tc' in 't' * 3 + 'c' * 3 + 'g' * 3 + 'a' * 3 True The second variation demonstrates that * has a higher precedence than +, and + has a higher precedence than in.

In defining a vocabulary, it is natural to define some of its words in terms of others. Python provides a small initial set of words, and you expand on that set by defining more of them. One reason for writing small functions is that simple functions are easier to write and test than complicated ones. If function A calls B, and B calls C, and C calls D, but something isn’t working in D, you can call D yourself from the interpreter. Once you’re sure that D works, you can call C, and so on. Another reason for defining a separate function for each action is that a very focused function is likely to prove more useful in other definitions than a larger multipurpose one.

For instance, parentheses could be used as follows to make the result of the preceding example be 17: >>> (4 + 2) * 3 − 1 17 Comparisons can be combined to form “between” expressions: >>> 1 < 4 < 6 True >>> 2 <= 2 < 5 True >>> 2 < 2 < 5 False Strings can participate in sequences of operations: >>> 'tc' in ('ttt' + 'ccc' + 'ggg' + 'aaa') True >>> 'tc' in 't' * 3 + 'c' * 3 + 'g' * 3 + 'a' * 3 True The second variation demonstrates that * has a higher precedence than +, and + has a higher precedence than in.

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