LaTEX Introduction 2: Simple Math

LaTEX is like a programming language. When you make document with LaTEX it is like you make a program. One of adavantages of LaTEX compared to other word processing softwares (especially a proprietary word processor) is its flexibility in mathematics formula writing. Of course, it is not trivial for beginners. In my experience, I need about 3 hours to make a very simple document with very basic mathematical expression.

There are a lot of sources on LaTEX in the internet. Just type a keyword on LaTEX in your search engine and then you will find abundance materials. If you just started and enjoy an example-based study, try this template and then do make an experiment by yourself.


% PREAMBLE (APPLIES TO WHOLE DOCUMENT) :
\documentclass[11pt]{article}

\usepackage{amsmath} % THESE THREE LINES SHOULD
\usepackage{amssymb} % BE KEPT IN EVERY DOCUMENT
\usepackage{latexsym} % YOU WRITE DURING THIS COURSE

\setlength{\textwidth}{16cm}
\setlength{\hoffset}{-2cm}
\setlength{\textheight}{24.5cm}
\setlength{\voffset}{-2cm}

\setlength{\parindent}{0cm}
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% END OF PREAMBLE

\begin{document}

\begin{center}
\textbf{Demonstration 2: Simple maths, 2008 -- 09}\\[3mm]
\today
\end{center}

\bigskip
% $ $ is for mathematical function
% ----- is for membuat tanda garis atau
% $-$ adalah tanda minus
% emph is for cetak miring
% int is for integral function
% | | is for absolute
% $$ for function

In the peptide identification using PMF, first of all, the sample was seeded in the Mass Spectrometry (MS) and then its mass spectrometric data was processed. The general processing steps are baseline (background) substraction, noise removal, peak picking, peak clustering, and de-isotoping. The data output of those steps is a peptide candidate list. This candidate list then will be compared to the database. The main key of the protein identification is the accuracy to produce peptide candidate list and time spent in database comparison. This report will use new approach. The theoretical spectrometric data will be developed based on the true peptide list after that is compared to real spectra data gotten from experiment. By using this approach the data processing which will be applied to experimental spectra data is only baseline (background) substraction.

The probability of isotope's position can be estimated by using Poisson distribution. The first peak is always assumed as monoisotope peak and then the adjacent peak with distance 1+error will be member of the group. This method also has been implemented in programmable computer systems, Field Programmable Gate Array, based.
$$
E(i,m_p)=\frac{a_p\,F(m_p)^i}{i!}; i=1,2,3,\ldots; E(i,m_p)>0, % Poisson Distribution for peptide
$$
and
$$
F(m_p)=0.000594\,m_p-0.03091,
$$
where $F(m_p)$ is maaping function of $m_p$, $E(i,m_p)$ is intensity of $i$-th, $m_p$ is monoisiotopic mass, $a_p$ is a monoisiotopic intensity at $m_p$,and $i$ is number of isotope in one cluster.

\end{document}