X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/chloroplast13.git/blobdiff_plain/023abe68272c9371d78a52331610cfd4c3602c5c..debf111706b70afb07c75b550973fa71fc2dcbce:/annotated.tex?ds=sidebyside

diff --git a/annotated.tex b/annotated.tex
index 52ce278..ad0f654 100644
--- a/annotated.tex
+++ b/annotated.tex
@@ -325,7 +325,7 @@ to align these sequences with each others.
 \end{figure}
 
 \section{Implementation}
-We implemented the three algorithms using dell laptop model latitude E6430 with 4 GB of memory and Intel core i5 processor of 2.6 Ghz and 3 MB of cash. We built the code using python version 2.7 under ubuntu 12.04 LTS. We also used python packages such as os, Biopython, memory\_profile, re, numpy, time, shutil, and xlsxwriter to extract core genes from large amount of chloroplast genomes. Table \ref{Etime}, show the annotation type, execution time, and the number of core genes for each method:
+We implemented the three algorithms using dell laptop model latitude E6430 with 6 GB of memory, and Intel core i5 processor of 2.5 Ghz$\times 4$ with 3 MB of CPU cash. We built the code using python version 2.7 under ubuntu 12.04 LTS. We also used python packages such as os, Biopython, memory\_profile, re, numpy, time, shutil, and xlsxwriter to extract core genes from large amount of chloroplast genomes. Table \ref{Etime}, show the annotation type, execution time, and the number of core genes for each method:
 
 \begin{center}
 \begin{tiny}
@@ -355,12 +355,12 @@ The second important factor is the amount of memory usage in each methodology. T
 \caption{Memory usages in (MB) for each methodology}\label{mem}
 \begin{tabular}{p{2.5cm}p{1.5cm}p{1cm}p{1cm}p{1cm}p{1cm}p{1cm}p{1cm}}
 \hline\hline
-Method& & Load Gen. & Conv. gV & Read gV & ICM & Gen. tree & Core Seq. \\
+Method& & Load Gen. & Conv. gV & Read gV & ICM & Core tree & Core Seq. \\
 \hline
 Gene prediction & ~ & ~ & ~ & ~ & ~ & ~ & ~\\
 \multirow{2}{*}{Gene Features} & NCBI & 15.4 & 18.9 & 17.5 & 18 & 18 & 28.1\\
               & DOGMA& 15.3 & 15.3 & 16.8 & 17.8 & 17.9 & 31.2\\
-Gene Quality  & ~ & 15.3 & $\le$200 & 16.1 & 17 & 17.1 & 24.4\\ 
+Gene Quality  & ~ & 15.3 & $\le$3G & 16.1 & 17 & 17.1 & 24.4\\ 
 \hline
 \end{tabular}
 \end{table}
