Bio-Python

Exploratory programming using iPython

chirag740@gmail.com — Sun, 05 May 2013 01:18:14 PDT

Python is an interactive shell for the Python programming language.
iPython offers several additional and useful options:

Better introspection
Additional shell syntax (magic commands that begin with % sign)
Tab completion
allows to record history

To install iPython visit : ipython.org/install

iPython has following three interfaces:

In linux terminal type "ipython qtconsole". This will launch a new Qt based window, similar to teminal.

The following magic functions are currently available: (These commands can also be found by typing %quickref in iPython shell)

Why Bio-python is not active recently?

chirag740@gmail.com — Sun, 07 Apr 2013 14:22:38 PDT

If you visit Bio-Python regularly, you would have noticed that recently there are no new posts on this blog. I am recently contributing my spare time to develop "PlaySeeBow.com" and related android application "Prescribd". Playseebow is under pilot studies and will be unraveled for access to masses.

Don't worry, Bio-Python isn't going away.;Once Playseebow is up and running, posts will commence once again.

Python 3: Filter function and list comprehensions

chirag740@gmail.com — Thu, 28 Feb 2013 07:26:14 PST

Many of you who are familiar with python 2 and have switched to python 3 may already know that functions (filter, map, range etc.) that returned a list no longer do so. In python 3, these functions return an iterator.
In case you wish to use filter, map etc. and get a list in python 3, you have two techniques at your disposal, namely:

Wrap the iterator around list( )
Use list comprehensions instead

Wrapping the iterator around list

The following snippets returns all even numbers upto but not including 10.

Using list comprehension technique

We can modify the above program to do the same task but using more familiar list comprehension method.

This also gives us all even number upto but not including 10.

Leave a comment explaining how there two coding styles differ in efficiency and readability?

Checking 'nan' and 'inf', pythonic way

chirag740@gmail.com — Tue, 26 Feb 2013 14:27:19 PST

How to check for Not a Number (NaN) or Infinity (Inf) in python?

NaN:

In python you can declare 'nan' as a float.

Inf:

When you try print(1E650), it returns inf. In python, variable x can be checked for 'inf' using math.isinf(x)

For more on 'nan' and 'inf' refer PEP 754.

Preference of language in scientific computing - why we speak python more often now

chirag740@gmail.com — Thu, 28 Feb 2013 05:24:47 PST

"Exploratory programming" is the most appropriate word. It aptly describes scientists (of non-Computer Science background) who do computation, but they never know beforehand which implementation will lead to an answer. When Fortran was language of choice in scientific computing data generation was the central focus. With advancement of human knowledge in various fields of science, data processing became equally if not more important. The role of biologists and chemists doing computation has evolved over years until today when they (researchers) are typically required to perform numerical calculations on one hand, as well as carry out diverse tasks like administering databases, procuring information from them, managing workflows etc. Therefore implementing python in such scenario is most viable option.

Another important reason for popularity of python was explained by Eddie Cao (Sr. Informatics Architect at Novartis) during US-PyCon 2012 "... For us python has lot of advantages, at the top of my mind is the fact that python is very approachable. We support scientists that are not computer scientists by training. They are chemists and biologists, but they can actually look at python code and make so many changes."

The legacy code which has been written in other languages like Fortran and MATLAB⁺ etcetra is time tested. Python works as a glue by perform mapping of the data structures in the classical (legacy) codes. For example, F2py which makes it possible to wrap complete Fortran modules.

Much of the useful code in science and engineering is already written in languages like Fortran and MATLAB⁺.

Some python based projects :

Though this list can be very long but here are a few projects that are popular and/or I find of some personal interest.

Project	Description	Website
NumPy	provides support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays	http://numpy.org/
SciPy	Library for mathematics, science, and engineering. It in turn depends of numpy which provides array manipulation libraries.	http://scipy.org/
iPython	Interactive Python consists of three interfaces: Shell based QtConsole and Web based Notebook	http://ipython.org/
Matplotlib	2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms	http://matplotlib.org/
MayaVi	3D plotting library	http://mayavi.sourceforge.net/
Pandas	library providing high-performance, easy-to-use data structures and data analysis tools	http://pandas.pydata.org/
PyQuante++	suite of programs for developing quantum chemistry methods. written in python, numerical python and C	http://pyquante.sourceforge.net/
MMTK	a.k.a. Molecular Modelling Toolkit	http://dirac.cnrs-orleans.fr/MMTK/
BioPython	set of tools for biological computation	http://biopython.org/

⁺ MATLAB is a registered trademark of The MathWorks, Inc.
⁺⁺ Rate limiting steps in PyQuante are written in C. If sometime in future, you expect to see a complete Python based Quantum Chemistry program, you must consider contributing some money towards fund raising for PyPy project. I really do not know if that is an exaggeration, but developers at PyPy are known for doing some crazy stuff (including development of a faster although restricted form of Python!).

Python-3 GUI. What developer options exist?

chirag740@gmail.com — Mon, 25 Feb 2013 21:51:46 PST

After reading article about "file reading and copying", few readers via comments on g+ and email asked to write about GUI development in python 3. Frankly, I have never been GUI fan but for the sake of requests I explored some development options available. My preference is summarized below:

For python 2.7 : wxPython > pyQt > tkinter
For python 3.x : PyQt > tkinter (no WxPython support while the time of writing this)

There are more options available which I have not explored yet. (An exhaustive list can be found here: GUI programming.)

First and foremost, I'd like to say that wxPython is one of the best project as per my literature survey (notably, GvR quoted it to be most mature GUI project) but since it has not been ported into python 3.x, I will talk only about PyQt4. WxPython is under very active development and hopefully soon it will be released for py3k and its progenitors.

Why not show love for tkinter?

Yes, obviously it is native in python, stable and simple but what I don't like about tkinter is that it often tends to have a non-native look. Tkinter windows (or frames if u like to call it phuff!!) often look strikingly different from current theme. Secondly, unlike PyQt and WxPython, tkinter does not have a very active user community.

IDLE; python's own IDE is designed using tk. On my arch linux running XFCE desktop environment its frames appear noticeably different from that of other applications.

Importing ttk which is one way to address issue of incongruous appearance of tkinter. (but be aware, ttk alters the methods of tk widgets so don't be surprised if you cannot call select/deselect on a checkbutton with ttk.) Call me biased but I find pyQt and wxPython more tweak-able than tkinter.

Important note :

PyQt comes in two different license versions:

GPL (code must be made available)
Commercial license (costs money)

There's also PySide which is mostly but not completely compatible with PyQt and comes with less restrictive license (LGPL) that allows both open source and proprietary software development. This difference in license might be of great significance to those who seek to develop commercial application.

As of now, I only found PyQt4 as a mature project that is ready for python 3. If you are using other python GUI development tool, tell how it is superior than the ones mentioned here (tk, wxpython and pyqt). Also mention whether it is available for python 3. In coming weeks I will briefly summarize the PyQt4 modules and will show how to develop simple frames.

Proposal for "Bioinformatics & Computational Chemistry" on Stack Exchange Network

chirag740@gmail.com — Fri, 22 Feb 2013 00:14:46 PST

I cordially invite you to help create a "Bioinformatics & Computational Chemistry" community on Stack Exchange. Stack Exchange is a fast-growing network of question and answer sites. Participating in the Q&A system, you can:

Ask questions in any area within or across Computational chemistry\biology disciplines
Find if others have questions that you have encountered in your research or professional career and answer them
Vote for questions and answers
Build reputation as a Bioinformatics or Computational Chemistry expert
Help build a knowledge-base for computational chemistry\biology

Let us create a visible, sustainable and open community of chemistry and biology using StackExchange.

Why StackExchange?

It is easy to put up a Q&A system, but it is much more difficult to develop a successful sustainable community. StackExchange forces a community to build, and prove itself by the commitment of users to the StackExchange Communities. This is done through it's Area51 process.

How to Participate?

To create a Bioinformatics and Computational Chemistry Q&A community hosted by StackExchange, we need to demonstrate participation, and generate a sustained flow of Q&A exchanges. The intial steps are:

Visit : http://area51.stackexchange.com
Create an account : click here (opens in new tab)
Go to the "Bioinformatics and Computational Chemistry" proposal: click here
Click "Follow It!"
Ask example questions. Your reputation grows as your questions and comments are voted up by other users. Discuss whether questions posted by others is suitable for the community.
Vote for questions. You help others earn a reputation..

Stages:

Definition ===> Commit ====> Beta ====> StackExchange site

(Currently this community is in definition phase.)

I hope you find "Bioinformatics and Computational Chemistry" community useful and it achieves the "COMMIT" status soon.

CRITERIA FOR THE “BETA” STATUS: 200 participants; 100 participants with 100+ reputation points on other StackExchange sites

CRITERIA FOR STACKEXCHANGE SITE: 15 questions a day; 90% questions answered; hundreds of users; more than one answer per question; 1500 visits a day

www.hypersmash.com

Reading a file and how to make a copy of a file in Python 3.x

chirag740@gmail.com — Mon, 18 Feb 2013 23:46:32 PST

Today, I'm going to write about ways of reading contents of a file using python 3. There are two common ways to do this. A not so good way and a better way. Further, we will also see how to copy contents of one file into other file.

We will work with a file named "acetylene.xyz". The contents of this file is as follows:

Reading a file METHOD 1: Not so good way

Using try/ finally one can read as follows:

In the above code, we called inbuilt function open( ) which takes filename as a necessary argument. You can also provide 'r', 'w', 'a' i.e. read write append etc. as optional arguements. The function, open( ) also takes encoding ('UTF8', 'ASCII' etc.) as an optional argument.When you don't mention the encoding, python uses locale.getpreferredencoding( ) to determine your environment's default encoding.

Executing the above piece of codes indeed gives the expected output.

Reading a file METHOD 2: A better way

Here we will use the with statement which was introduced in python 2.5 as a replacement for try/finally (see PEP 343). We can read the same file using with statement as follows:

The above code gives the same output as method 1:

In Method 2, the file is open when you are within the code block of with statement. The moment you leave this code block, python closes the file for you by calling a_file.close( ). You don't have to do it yourself as in method 1.

Now you'd be wondering why I say that method 2 is better than method 1. Mark Pilgrim in his book Dive Into Python 3 explains as follows:

"Stream objects have an explicit close( ) method, but what happens if your code has a bug and crashes before you call close( )? That file could theoretically stay open for much longer than necessary. While you’re debugging on your local computer, that’s not a big deal. On a production server, maybe it is."

How to copy contents of one file into other file?

Using the above code, the file "acetylene.xyz" is copied into a backup directory. The name of backup file will also be acetylene.xyz (because we did not mention file name, backup was an already existing directory).

Acknowledgement
Special thanks to +wesley chun (author, core python programming) for his valuable suggestions on improving this post.

Choice of coordinate systems

chirag740@gmail.com — Mon, 18 Feb 2013 23:55:22 PST

One of the common questions often encountered in molecular modelling relates to the choice of representation between Cartesian coordinate and internal coordinate.

Cartesian coordinate: The position of atomic nuclei is described in three dimensional space using three variables x, y and z.

Cartesian coordinate of acetaldehyde can be presented as follows:

Internal (Z-matrix) : When talking of Z-matrix, we keep track of relative position of atoms. Z-matrix is composed of atom number, bond length, bond angle and dihedral angle.
Z-matrix for acetaldehyde:

Therefore, one can say that the basic difference between the two representations is that the Cartesian coordinate is an absolute way of describing position, whereas Z-matrix is a relative.

When is Z-matrix better than Cartesian?

Z-matrix is very useful while optimizing a structure by keeping some restraints. For example, optimizing the structure for minimum energy by keeping a particular dihedral angle within certain range of value. Z-matrix is also useful when dealing with molecules like water (C_2v symmetry) and ammonia (C_3v symmetry). In ammonia three hydrogen atoms are pyramidal and equivalent. Using z-matrix you can tell the program about the fact that ammonia is C_3vsymmetric by giving proper constraints and the molecule will indeed be optimized accordingly.
However, Cartesian coordinates should generally be preferred when dealing with non-symmetric molecule or very large molecule (to reduce error due to rounding off).

How to convert Cartesian to Z-matrix?

The recipe from converting Cartesian coordinates into Z-matrix consists following two elements.

Bonds which are calculated as Euclidean distances.
Angles that are determined using the following equation:

\cos ϕ = \frac{(x_{0} - x_{1}) . (x_{2} - x_{1})}{|x_{0} - x_{1}| |x_{2} - x_{1}|}

In the above equation, torsional angle is the angle made by two planes. One comprising of points X₀, X₁ and X₂and other comprising of points X₁, X₂and X₃ respectively. These two planes can be imagined as in the figure below.

Dihedral angle formed by two plane as described above

Some programs that are used for such conversions include OPEN-BABEL and newzmat (in Gaussian).

Which coordinate system do you prefer? Participate in the poll below.

When do you use Z-matrix and when do you prefer Cartesian? Leave a comment and share the rationale behind your choice of coordinate system.

Golden Jubilee of Ramachandran Plot

chirag740@gmail.com — Thu, 21 Feb 2013 13:47:12 PST

Exactly fifty years from now i.e. in the year 1963, G. N. Ramachandran et. al published breakthrough original research in Journal of Molecular Biology. Ramachandran plot still remains a touchstone for protein form and structure (for example, its use in validating homology models). This plot is remarkable because it came ahead of time. It was proposed in 1963 when there were no computers, mechanical calculators were the cutting edge of technology!

Backbone conformations of: (A) glycine and (B) pre-proline. Backbone schematic and observed Ramachandran plot of (A) glycine and (B) pre-proline. Taken from the data-set of Lovell et al. (2003). The clustered regions are labeled on the Ramachandran plots.

Late Prof. Ramachandran (affectionately called GNR) established Molecular Biophysics Unit (MBU) at Indian Institute of Science (IISc), Banglore in 1971. Following the footsteps of his mentor Dr. C.V. Raman, G. N. Ramachandran carried out most of his research in India. To mark the celebration of 50 years of Ramachandran map MBU organized "International Conference on Biomolecular Forms and Fuctions" from 8^th - 11^th January 2013. (official website: http://icbff2013.com/)

Several eminent scientists including Professor Tom Blundell and Professor J. Andrew McCammon delivered their talk during the conference.

Some interesting references:

1. Kleywegt GJ, Jones TA. Phi/psi-chology: Ramachandran revisited. Structure. 1996 Dec 15;4(12):1395-400. PubMed PMID: 8994966.

2. Lovell SC, Davis IW, Arendall WB 3rd, de Bakker PI, Word JM, Prisant MG, Richardson JS, Richardson DC. Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins. 2003 Feb 15;50(3):437-50. PubMed PMID: 12557186.

Configuring Emacs as Python IDE

chirag740@gmail.com — Wed, 27 Feb 2013 14:41:23 PST

UPDATE: The following article applies only to python 2.7 (because ropemacs for py3k is not available).

This article illustrates the idea presented in emacs article that I wrote four month ago and can be found here.

I have compiled lisp codes that will be useful for anyone who is programming in python and is using emacs. At present there is no particular IDE that offers full functionality (syntax highlighting, auto-complete, refactoring etc.) So, I decided to built one using emacs.

I am using a configuration which is variant of what is described in following two pages:

1. Original article about python emacs integration can be found at enigmacurry.com

2. A more detailed and recent step by step article can be found jesshamrick.com

To download my ~/.emacs and ~/.emacs.d/ configuration for Python programming environment see emacs-config-pythonists repository.

What I like the most about python-mode in emacs is the ability to execute current buffer on doing C-c C-c.

Try it yourself and do share your useful comments and suggestions for improvements. I would like to know how many of you (readers) have tried python development using vim/emacs (no flame wars here!). If you have ever tried scripting python using emacs share your views. Describe ease (and annoyances) in emacs by leaving a comment. If you use any other full-fledged IDE participate in the poll below.

QSAR: All models are wrong, but some are useful

chirag740@gmail.com — Mon, 18 Feb 2013 23:45:09 PST

The core of the QSAR methodology is developing a relationship between an observed activity and structural features of a molecule. The approach depends on being able to represent the structure of a molecule in quantitative terms. The quantitative representations of molecules are termed descriptors. An extensive range of descriptors can be calculated; for example, molecular weight, atom counts, partition coefficients and surface-property descriptors. So given a set of descriptors, a QSAR model can be built by defining a relationship between these descriptors and the observed activity.

Why to establish QSAR?

• To predict biological activity and physicochemical properties by rational means.

• To understand the mechanisms of action within a series of chemicals.

• To identify novel leads with pharmacological, biocidal or pesticidal activity.

• The selection of compounds with optimal pharmacokinetic properties, its stability or availability in biological systems.
• The prediction of toxicity to humans and environmental species.

CLASSIFICATION OF QSAR METHODS

Based on the type of chemometric methods used QSAR methods are classified as linear and non-linear as shown in Figure 1.

LINEAR METHODS: The first QSAR models, developed by Hansch, specified linear relationships. Linear models are widely used owing to their simplicity and ease of development. Linear methods for example linear regression (LR), multiple linear regression (MLR), stepwise multiple linear regression (S-MLR), partial least-squares (PLS), and principal component analysis (PCA).

NON-LINEAR METHODS: Developments in the field of statistics have produced many new methods of building predictive models. These include non-linear regression and algorithmic techniques. These include support vector machine (SVM), artificial neural networks (ANN), k-nearest neighbors (kNN), and Bayesian neural nets (BNN) etc.


Figure 1. Classification of QSAR methods

QSAR methods are also categorized into following classes, based on the way by which the descriptor values are developed (figure 1):

0D-QSAR is achieved based on descriptors derived from molecular formula such as molecular weight, number of atoms, atom types, sum of atomic properties;

1D-QSAR (correlates activity with global molecular properties like pKa, solubility, log P, functional groups(substructures) etc);

2D-QSAR (correlates activity with structural patterns like connectivity indices, 2D-pharmacophores wiener index, etc., without taking into account the 3D-representation of these properties);

3D-QSAR (deals with the orientation of the molecules in space, correlates activity with non-covalent interaction fields “steric and electrostatic field” surrounding the molecules);

4D-QSAR (additionally including ensemble of ligand configurations in 3D-QSAR, by representing each molecule in different conformations, stereoisomer’s, orientations, tautomer’s, or protonation states.);

5D-QSAR (explicitly representing different induced-fit models in 4D-QSAR, as the manifestation and magnitude of the induced fit may vary for binding of individual molecule to target protein);

6D-QSAR (further incorporating different solvation models in 5D-QSAR, can be achieved explicitly by mapping parts of the surface area of the molecules with solvent properties); HiT QSAR (hierarchical quantitative structure–activity relationship technology) based on the Simplex representation of molecular structure (SiRMS) and its application for different QSAR tasks. The spirit of this technology is a sequential solution (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of molecular structure description [from one dimensional (1D) to four dimensional (4D)].

QSAR: Basic Steps Involved

The QSAR model development trail involves four steps:

(a) Data collection and descriptor calculation,

(b) Analysis of correlation between the descriptors and input data structures (2D/3D),

(c) Validation of models and

(d) Design and activity prediction of new molecules.

For the development of a QSAR model, series (con-generic series in some cases e.g. CoMFA/CoMSIA, 3D-QSAR methods) of molecules, defined by their structures, with known activity data are used as input data for calculation of molecular descriptors. For all the compounds, the activity data should be in same units of measurement (binding/functional/IC50/Ki). Ki value is preferred instead of the IC50 data, since it is independent of the substrate concentration. To develop a QSAR, a significant number of compounds are requisite to develop a meaningful relationship. It is widely accepted that 5 to 10 compounds are required for every descriptor in a QSAR. This does suggest that a 1 descriptor regression-based QSAR could be developed. However in an ideal world “many more” compounds are required to obtain statistically healthy QSARs.

The structure cannot be directly used for creating structure-activity mappings for reasons that they do not usually contain in an unambiguous form the information that relates to activity. To evade this barrier, rationally designed molecular descriptors convert the structure to well defined sets of numerical values that can be correlated directly with the activity. Depending on data set, amongst the thousands of different descriptors available, only a few are well correlated to the activity and hence, the use of excess number of descriptors may affect the interpretability of the final model. To avoid this problem in QSAR analysis, a wide range of techniques for automated thinning of the set of descriptors to the most informative ones are used. This is followed by the splitting of the dataset into training and test sets using different approaches of hierarchical and non-hierarchical clustering, which is based on many algorithms including sphere exclusion theory or simply activity ranking. However, according to some authors, such similarity based splitting methods may result in selection of a biased test set. Hence to overcome this, splitting may also be done based on random selection of subset molecules to generate test set data.

The training set compounds are then used for building a correlation between the descriptor values and the activity data. The resulting correlation is obtained using different chemometric tools (both linear and non-linear) like PLS, PCA, ANN, kNN etc and the model quality is judged using a variety of statistical parameters. Further, the model thus obtained undergoes both internal (leave-one-out method etc.) and external validation (test set prediction etc). The predictivity and reproducibility of the QSAR model is decided based on its ability to predict the test set molecules. A proper interpretation of a QSAR model exposes the key structural features obligatory for an improvement in the definite response parameter being modeled. Hence the developed model can be used further for design and activity prediction of new series of molecules.

QSAR is a widely used tool for developing relationships between the effects (activities and properties of interest) of a series of molecules with their structural properties. It is used in many areas of science. It is a dynamic area that integrates new technologies at a staggering rate.

Topics which I have discussed above were required to introduce you to QSAR. This is just the beginning; there is plenty to share about QSAR, it is not just a method where some steps are involved in developing model. I would like to discuss QSAR models and what they signify. I didn’t discuss it here since this is just an introduction. In future I will also discuss about ‘validation’. Validation of each step is important, if you don’t want to end up with an erroneous model. Even after model development, validation plays a vital role. Any QSAR study is as good as the model on which it is based.

In conclusion I would say that usefulness of QSAR as a technique relies on generation of more robust models, which is the next big challenge.

“Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.”

- George E. P. Box

This article is contributed by +PRAVIN AMBURE who is presently a Junior Research Fellow at Dr. Kunal Roy Lab at Jadavpur University, Kolkata. Pravin's research work is generating QSAR models with better predictability. In his spare time he likes solving Rubik’s cube.

Emacs or: How I stopped worrying and started using "meta" key

chirag740@gmail.com — Mon, 18 Feb 2013 23:43:00 PST

After installing ubuntu on my notebook lately, I decided to begin using software that I always despised. Unbelievably, first target on my list was a text editor. A text editor! How can someone hate using a text editor? I did. Its name was emacs.

Downloading and installing latest version of emacs was a piece of cake, since emacs was available via Ubuntu Software Centre. With all my arsenals ready, akin to a real Jedi; I commenced my quest to explore emacs. Although there are numerous open-source text editors available, I chose emacs since it has a large user base (and hence many communities of programmers as well as hackers, willing to help me out in using it). Emacs and vi happen to be adversaries in the so called “editor war”, a term ascribed to the long-going tussle between the users of the two editors. Aficionados of either software never forsake any opportunity to show that their program's editing capability is flawless in every possible way (of course an exaggeration, we are far away from any such utopia, if it exists!).

Which is best among equals? A never ending debate.

Well, frankly vi (as well as vim a.k.a. vi improved) is light-weight and fast as compared to emacs. Still, extensive range of shortcut keys in emacs makes it a handy tool to deal with data. Infact, due to its obscure shortcuts, vi saviors often ridicule emacs by presenting EMACS as acronym for "Elsewhere Maybe All Commands Simple". Though, emacs is associated with a complex learning curve as shown below, it pays-off all the time and energy invested in learning it, when you actually put its features into practice.

No matter what haters say, the fact remains that emacs is an effective tool for those who deal in copious amounts of data. One of the reason why most people find it difficult to acquaint themselves with emacs is that it has too many shortcut keys which are sometimes fussy. To make things worse, emacs documentation uses parlance that is unfamiliar to newcomers from windows environment. For example: emacs documentation tells to use M-% to perform a “query-replace”. Windows users can never guess, that letter M in “M-%” is meta-key which is nothing but “alt” key on windows keyboard. On unix keyboard it is represented by [♦] key.

Unix keyboard from Sun Micosystems (meta key is encircled)

Some useful emacs shortcuts are given in following pdf document (download it, print it and keep it handy):

Mol Modelling Emacs
Several default features in emacs are quite different from regular text editors. For example, if you select some text and press delete key, the text does NOT disappear. To make this behaviour similar to other standard text manipulators, you need to alter the .emacs file in your home directory.

For those running on linux, press C+M+t (i.e. control+alt +t in emacs lexicon) and in terminal type "emacs ~/.emacs" (without quotes)
and add the following lines to .emacs file:

The above code is written in a language called “lisp”, which emacs uses to understand its user customized behaviour. Statements followed by double semicolons (;;) are comments in lisp and will not be read by emacs. You may skip adding them.

You may consider adding the following lisp code too, to further customize emacs:

It is also possible to use emacs akin pico (i.e. within terminal). Go to terminal and type "emacs -nw" (no quotes)

It is a good idea to make an alias named emacsx (or whatever you wish) for the command emacs -nw and place it in your ~/.bashrc file.

To learn more about emacs I suggest, using the website emacswiki.org, it is bible of emacs. Series of screencast by Kurt Schwehr will also be useful for beginners.

For me, learning emacs, turned out to be a breath of fresh air. Hope it will be same for you.

Happy Editing...

(C-x C-c / Good Bye!)