<?xml version='1.0'?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:atom="http://www.w3.org/2005/Atom" >
<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/31377?offset=1010</link>
	<atom:link href="https://bioinformaticsonline.com/related/31377?offset=1010" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	
<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29883/ra-bioinformatics-at-school-of-computational-integrative-sciences-jnu-india</guid>
  <pubDate>Fri, 18 Nov 2016 03:57:56 -0600</pubDate>
  <link></link>
  <title><![CDATA[RA Bioinformatics at School of Computational &amp; Integrative Sciences, JNU, India]]></title>
  <description><![CDATA[
<p>School of Computational &amp; Integrative Sciences<br />Jawaharlal Nehru University<br />New Delhi – 110067</p>

<p>Date: Nov 11th. 2016                                                            Last Date:  Nov 25th. 2016</p>

<p>PROJECT ID: 632</p>

<p>The following posts are urgently required to be filled for the Department of Biotechnology, Government of India funded project entitled "Computational Core for Plant Metabolomics" administrated by Prof Indira Ghosh,  School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi-110 067</p>

<p>NB:For all Bioinformatics posts, preference will be given to candidates with a good knowledge of Python and/or R. Knowledge of JAVA will also get a special consideration.</p>

<p>RA / Research Associate (Metabolic engineering/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA<br />Vacancy: 1<br />Essential Qualifications: PhD in  Bioinformatics /Mathematics/Computer Science with experience in analyzing high throughput omics-based data/ system Biology/ Analysis of Network Biology. Published paper in the field is a must to prove the experience.<br />Desired Skills: Prior experience in handling and guiding bioinformatics, metabolomics data, planning of new research area in metabolic driven network , managing the project portal, preparing and filing reports etc. Will be expected to communicate with user groups and coordinate with LIMS group in Hyderabad and the Cheminformatics group in Delhi.</p>

<p>RA / Research Associate (Chemo-informatics/Computational Biologist)</p>

<p>Salary: Rs. 36000/- + HRA<br />Vacancy: 1<br />Essential Qualifications: PhD in Bioinformatics/ computational biology/ Biophysics/Computer Science. Computational and Chemical structure related experience is a necessary qualification proven by paper published and program developed. <br />Desired Skills:  Research experience in Chemical scaffold mapping, in silico Spectral analysis, Biological Database Designing &amp; Integration is required. Individual is responsible to develop methods related to metabolite identification, Testing and refining and integrate LIMS with IIIT Hyderabad and will be expected to communicate with user groups.</p>

<p>Project SRF (Bioinformatics/Programming)</p>

<p>Salary: As per DBT rules<br />Vacancy: 1<br />Essential Qualifications: Masters/B Tech in Basic Sciences with at least 2yrs of research experience in Bioinformatics/Computational Biology related to Database /portal building &amp; maintenance ,high throughput data handling and analysis etc. For M.Sc/B.Tec, Published paper  in peer-reviewed Journal and for M.Tech, thesis submission in computational biology is a must.</p>

<p>More at http://www.jnu.ac.in/Career/currentjobs.htm</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</guid>
	<pubDate>Thu, 23 Jul 2020 05:49:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41996/wgd%E2%80%94simple-command-line-tools-for-the-analysis-of-ancient-whole-genome-duplications</link>
	<title><![CDATA[wgd—simple command line tools for the analysis of ancient whole-genome duplications]]></title>
	<description><![CDATA[<p><span>wgd is a easy to use command-line tool for<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>distribution construction named wgd. The wgd suite provides commonly used<span>&nbsp;</span></span><em>K</em><sub>S</sub><span><span>&nbsp;</span>and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner.</span></p>
<p><a href="https://academic.oup.com/bioinformatics/article/35/12/2153/5162749">https://academic.oup.com/bioinformatics/article/35/12/2153/5162749</a></p><p>Address of the bookmark: <a href="https://github.com/arzwa/wgd" rel="nofollow">https://github.com/arzwa/wgd</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/29998/csir-nehru-science-postdoctoral-research-fellowship</guid>
  <pubDate>Tue, 29 Nov 2016 12:34:59 -0600</pubDate>
  <link></link>
  <title><![CDATA[CSIR Nehru Science Postdoctoral Research Fellowship]]></title>
  <description><![CDATA[
<p>CSIR Nehru Science Postdoctoral Research Fellowship</p>

<p>About Fellowship: <br />CSIR Nehru Science Postdoctoral Research Fellowship Scheme is an Research Fellowship awarded/given by HRD Ministry, Govt. of India every year to more than 100 fellows.</p>

<p>It was started to identify promising and young researchers with novel ideas and provide them research opportunities in the areas of basic science, engineering, medicine &amp; agriculture.</p>

<p>The fellowship aims at facilitating their transition from mentored to independent research career.</p>

<p>In addition, check these ICTS Research Fellowships:<br />1.) Max-Planck Partner Group Fellowships 2017-18<br />2.) ICTS-Simons Postdoctoral Fellowships 2017<br />3.) ICTS Post Doctoral Fellowships 2017<br />4.) Airbus Prize Postdoctoral Fellowship 2017-18</p>

<p>Eligibility: To be eligible for this fellowship, you:<br />1.) PhD degree (within 3 years of award of PhD degree), OR<br />2.) Those who have submitted PhD theses.<br />3.) Applicants should have research publications in good impact factor SCI journals.<br />4.) Indian nationals, Persons of Indian Origin (PIO) &amp; Overseas Citizen of India (OCI), a can also apply.<br />5.) Maximum Age Limit: 32 years.</p>

<p>Duration: <br />– 2 Years.<br />– extendable for a maximum of 1 more year based on performance.</p>

<p>Remuneration: <br />– Rs. 50,000/- per month plus House Rent Allowance (HRA)<br />– A contingency grant of Rs. 3.0 lakh per annum.<br />– 25% of the contingency grant can be used for domestic and international travel.</p>

<p>Mode of Selection: You can apply throughout the year, but selection will be made twice a year, in June and December.</p>

<p>How to Apply: <br />– Read the instructions, given at Annexure-I in this PDF file.<br />– And, application form is given as, Annexure-II.<br />– Fill the form &amp; send it to the given address in the PDF file.</p>

<p>Deadline: Rolling Deadline (Applications accepted throughout the year)</p>

<p>Also See: Research Internship/ Fellowship in India:<br />1.) IIT Bombay Research Internship Awards Programme 2016-17<br />2.) IIT Delhi Internship Program 2016-17<br />3.) DAAD WISE – International Internship in Germany<br />4.) Summer Research Fellowship Programme| JNCASR Bangalore<br />5.) Indian Academy of Sciences Summer Internships 2017<br />6.) Winter Internship – IIT Bombay NPDE-TCA<br />7.) Viterbi – India Program 2017 | Research Internship in US<br />8.) Internship – Centre for Stem Cell Research, Vellore</p>

<p>Accommodation &amp; other benefits: <br />– Accommodation may be provided by CSIR, if available.<br />– Medical benefits as per CSIR norms.</p>

<p>For more details: <br />– Check this PDF Notification of Fellowship.<br />– List of CSIR Labs &amp; their work/activities can be seen at www.csir.res.in.</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</guid>
	<pubDate>Wed, 18 Aug 2021 00:02:54 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43268/kmer-a-suite-of-tools-for-dna-sequence-analysis</link>
	<title><![CDATA[Kmer: a suite of tools for DNA sequence analysis]]></title>
	<description><![CDATA[<p>More at&nbsp;https://help.rc.ufl.edu/doc/Kmer</p>
<p>This also includes:</p>
<ul>
<li>A2Amapper: ATAC, Assembly to Assembly Comparision tool:
<ul>
<li>Comparative mapping between two genome assemblies (same species), or between two different genomes (cross species).</li>
</ul>
</li>
</ul>
<ul>
<li>Sim4db:
<ul>
<li>Spliced alignment of cDNA and genomic sequences, from the same (sim4) or related (sim4cc) species. Optimized for high-throughput batched alignment.</li>
</ul>
</li>
</ul>
<ul>
<li>LEAFF:
<ul>
<li>LEAFF (ahem, Let's Extract Anything From Fasta) is a utility program for working with multi-fasta files. In addition to providing random access to the base level, it includes several analysis functions.</li>
</ul>
</li>
</ul>
<ul>
<li>Meryl:
<ul>
<li>An out-of-core k-mer counter. The amount of sequence that can be processed for any size k depends only on the amount of free disk space.</li>
</ul>
</li>
</ul><p>Address of the bookmark: <a href="https://help.rc.ufl.edu/doc/Kmer" rel="nofollow">https://help.rc.ufl.edu/doc/Kmer</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30027/dbt-india</guid>
	<pubDate>Sun, 04 Dec 2016 22:30:37 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30027/dbt-india</link>
	<title><![CDATA[DBT India]]></title>
	<description><![CDATA[<p>Latest announcement on DBT India.&nbsp;</p>
<p>Calls</p>
<p>Events</p>
<p>Projects</p>
<p>Jobs</p>
<p>&nbsp;</p><p>Address of the bookmark: <a href="http://www.dbtindia.nic.in/out-reach/latest-announcements/" rel="nofollow">http://www.dbtindia.nic.in/out-reach/latest-announcements/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43902/interactivenn-a-web-based-tool-for-the-analysis-of-sets-through-venn-diagrams</guid>
	<pubDate>Wed, 29 Jun 2022 03:22:26 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43902/interactivenn-a-web-based-tool-for-the-analysis-of-sets-through-venn-diagrams</link>
	<title><![CDATA[InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams]]></title>
	<description><![CDATA[<p><span>InteractiVenn, a more flexible tool for interacting with Venn diagrams including up to six sets. It offers a clean interface for Venn diagram construction and enables analysis of set unions while preserving the shape of the diagram. Set unions are useful to reveal differences and similarities among sets and may be guided in our tool by a tree or by a list of set unions. The tool also allows obtaining subsets&rsquo; elements, saving and loading sets for further analyses, and exporting the diagram in vector and image formats. InteractiVenn has been used to analyze two biological datasets, but it may serve set analysis in a broad range of domains.</span></p>
<p><span>More at&nbsp;https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0611-3</span></p>
<p><span><img src="https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12859-015-0611-3/MediaObjects/12859_2015_611_Fig1_HTML.gif?as=webp" alt="image" style="border: 0px;"></span></p><p>Address of the bookmark: <a href="http://www.interactivenn.net/" rel="nofollow">http://www.interactivenn.net/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/30331/16th-congress-of-the-european-society-for-evolutionary-biology-eseb</guid>
  <pubDate>Thu, 22 Dec 2016 08:08:37 -0600</pubDate>
  <link></link>
  <title><![CDATA[16th Congress of the European Society for Evolutionary Biology (ESEB)]]></title>
  <description><![CDATA[
<p>Abstract submissions for our upcoming symposium on the Genomics of Adaptation that will take place as part of the 16th Congress of the European Society for Evolutionary Biology (ESEB). The conference will take place from August 20th - August 25th, 2017 in Groningen, the Netherlands. </p>

<p>SYMPOSIUM DESCRIPTION: Genomics of Adaptation [S16] Model organisms for life-history research are mainly studied in the lab where functional genetics is assessable. In general, however, knowledge about their eco-evolutionary dynamics, such as biotic interactions, is rare. By contrast, in organisms for which the ecology and adaptation strategies in the field are well known, we typically lack the appropriate genetic tools to investigate functionality. Advances in genomics and statistics as well as investments in evolutionary model organisms are now providing access to putatively adaptive genome-wide variation within species from across the tree of life. In this symposium, we focus on integrating life-history biology, genetics and evolutionary ecology in the genomics era. </p>

<p>We wish to (1) highlight the role of genetic architecture of complex traits, such as adaptations to biotic interactions or life-history traits; (2) contrast this to morphological traits which are generally thought to have a less complex genetic architecture; and (3) discuss the opportunities and drawbacks of specific model systems. </p>

<p>INVITED SPEAKERS: Josephine Pemberton, University of Cambridge (http://bit.ly/2hJWytJ ) Peter Tiffin, University of Minnesota (http://bit.ly/2hK7HuS ) </p>

<p>ABSTRACT SUBMISSION The deadline for abstract submission is January 10, 2017. For more information and to submit abstracts online, please visit: http://bit.ly/2fBXlvN We look forward to an exciting symposium and seeing you all in Groningen! Sincerely, Ben Blackman, UC Berkeley Maaike de Jong, University of Bristol Bart Pannebakker, Wageningen University Noah Whiteman, UC Berkeley Jelle Zandveld, Wageningen University</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30375/mauve-a-system-for-constructing-multiple-genome-alignments-in-the-presence-of-large-scale-evolutionary-events-such-as-rearrangement-and-inversion</guid>
	<pubDate>Sat, 24 Dec 2016 09:20:53 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30375/mauve-a-system-for-constructing-multiple-genome-alignments-in-the-presence-of-large-scale-evolutionary-events-such-as-rearrangement-and-inversion</link>
	<title><![CDATA[Mauve: a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion]]></title>
	<description><![CDATA[<p>Mauve is a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion. Multiple genome alignments provide a basis for research into comparative genomics and the study of genome-wide evolutionary dynamics.</p>
<p>Mauve has been developed with the idea that a multiple genome aligner should require only modest computational resources. It employs algorithmic techniques that scale well in the lengths of sequences being aligned. For example, a pair of&nbsp;<em>Y. pestis</em>&nbsp;genomes can be aligned in under a minute, while a group of 9 divergent Enterobacterial genomes can be aligned in a few hours. However, the current algorithm&rsquo;s compute time (progressiveMauve) scales cubically in the number of genomes to align, making it unsuitable for datasets containing more than 50-100 bacterial genomes.</p><p>Address of the bookmark: <a href="http://darlinglab.org/mauve/mauve.html" rel="nofollow">http://darlinglab.org/mauve/mauve.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</guid>
	<pubDate>Mon, 27 Nov 2017 07:58:49 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/34416/miniasm-very-fast-olc-based-de-novo-assembler-for-noisy-long-reads</link>
	<title><![CDATA[miniasm: very fast OLC-based de novo assembler for noisy long reads]]></title>
	<description><![CDATA[<p>Miniasm is a very fast OLC-based&nbsp;<em>de novo</em>&nbsp;assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>) as input and outputs an assembly graph in the&nbsp;<a href="https://github.com/pmelsted/GFA-spec/blob/master/GFA-spec.md">GFA</a>&nbsp;format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final&nbsp;<a href="http://wgs-assembler.sourceforge.net/wiki/index.php/Celera_Assembler_Terminology">unitig</a>&nbsp;sequences. Thus the per-base error rate is similar to the raw input reads.</p>
<p>So far miniasm is in early development stage. It has only been tested on a dozen of PacBio and Oxford Nanopore (ONT) bacterial data sets. Including the mapping step, it takes about 3 minutes to assemble a bacterial genome. Under the default setting, miniasm assembles 9 out of 12 PacBio datasets and 3 out of 4 ONT datasets into a single contig. The 12 PacBio data sets are&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-Bacterial-Assembly">PacBio E. coli sample</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS473430">ERS473430</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS544009">ERS544009</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS554120">ERS554120</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS605484">ERS605484</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS617393">ERS617393</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS646601">ERS646601</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS659581">ERS659581</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS670327">ERS670327</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS685285">ERS685285</a>,&nbsp;<a href="http://www.ebi.ac.uk/ena/data/view/ERS743109">ERS743109</a>&nbsp;and a&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/E.-coli-20kb-Size-Selected-Library-with-P6-C4/ce0533c1d2a957488594f0b29da61ffa3e4627e8">deprecated PacBio E. coli data set</a>. ONT data are acquired from the&nbsp;<a href="http://lab.loman.net/2015/09/24/first-sqk-map-006-experiment/">Loman Lab</a>.</p>
<p>For a&nbsp;<em>C. elegans</em>&nbsp;<a href="https://github.com/PacificBiosciences/DevNet/wiki/C.-elegans-data-set">PacBio data set</a>&nbsp;(only 40X are used, not the whole dataset), miniasm finishes the assembly, including reads overlapping, in ~10 minutes with 16 CPUs. The total assembly size is 105Mb; the N50 is 1.94Mb. In comparison, the&nbsp;<a href="https://github.com/PacificBiosciences/Bioinformatics-Training/wiki/HGAP">HGAP3</a>produces a 104Mb assembly with N50 1.61Mb.&nbsp;<a href="http://lh3lh3.users.sourceforge.net/download/ce-miniasm.png">This dotter plot</a>&nbsp;gives a global view of the miniasm assembly (on the X axis) and the HGAP3 assembly (on Y). They are broadly comparable. Of course, the HGAP3 consensus sequences are much more accurate. In addition, on the whole data set (assembled in ~30 min), the miniasm N50 is reduced to 1.79Mb. Miniasm still needs improvements.</p>
<p>Miniasm confirms that at least for high-coverage bacterial genomes, it is possible to generate long contigs from raw PacBio or ONT reads without error correction. It also shows that&nbsp;<a href="https://github.com/lh3/minimap">minimap</a>&nbsp;can be used as a read overlapper, even though it is probably not as sensitive as the more sophisticated overlapers such as&nbsp;<a href="https://github.com/marbl/MHAP">MHAP</a>&nbsp;and&nbsp;<a href="https://github.com/thegenemyers/DALIGNER">DALIGNER</a>. Coupled with long-read error correctors and consensus tools, miniasm may also be useful to produce high-quality assemblies.</p>
<p>Minimap and miniasm are ultrafast tools for (i) mapping and (ii) assembly. Designed for long, noisy reads, they do not have a correction or consensus step, and therefore the resulting assemblies are contiguous (i.e. long) but very noisy (i.e. full of errors)</p>
<p>We start with an all against all comparison:</p>
<div>
<pre><code>minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq | gzip -1 &gt; reads.paf.gz
</code></pre>
</div>
<p>Then we can assemble</p>
<div>
<pre><code>miniasm -f reads.fq reads.paf.gz &gt; reads.gfa
</code></pre>
</div>
<p>Convert GFA to FASTA:</p>
<div>
<pre><code>awk <span>'/^S/{print "&gt;"$2"\n"$3}'</span> reads.gfa | fold &gt; reads.fa
</code></pre>
</div>
<p>And then count how many contigs:</p>
<div>
<pre><code>grep <span>"&gt;"</span> reads.fa | wc -l</code></pre>
</div>
<p>&nbsp;</p>
<pre><span><span>#</span> Download sample PacBio from the PBcR website</span>
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz <span>|</span> tar zxf -
ln -s selfSampleData/pacbio_filtered.fastq reads.fq
<span><span>#</span> Install minimap and miniasm (requiring gcc and zlib)</span>
git clone https://github.com/lh3/minimap <span>&amp;&amp;</span> (cd minimap <span>&amp;&amp;</span> make)
git clone https://github.com/lh3/miniasm <span>&amp;&amp;</span> (cd miniasm <span>&amp;&amp;</span> make)
<span><span>#</span> Overlap</span>
minimap/minimap -Sw5 -L100 -m0 -t8 reads.fq reads.fq <span>|</span> gzip -1 <span>&gt;</span> reads.paf.gz
<span><span>#</span> Layout</span>
miniasm/miniasm -f reads.fq reads.paf.gz <span>&gt;</span> reads.gfa</pre><p>Address of the bookmark: <a href="https://github.com/lh3/miniasm" rel="nofollow">https://github.com/lh3/miniasm</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/30654/source-code-and-pseudo-code</guid>
	<pubDate>Mon, 23 Jan 2017 10:17:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/30654/source-code-and-pseudo-code</link>
	<title><![CDATA[Source Code and Pseudo Code !!]]></title>
	<description><![CDATA[<p>An <span style="text-decoration: underline;">algorithm</span> is a procedure for solving a problem in terms of the actions to be executed and the order in which those actions are to be executed. An algorithm is merely the sequence of steps taken to solve a problem. The steps are normally "sequence," "selection, " "iteration," and a case-type statement.</p><p>In C, "sequence statements" are imperatives. The "selection" is the "if then else" statement, and the iteration is satisfied by a number of statements, such as the "while," " do," and the "for," while the case-type statement is satisfied by the "switch" statement.</p><hr><p><span style="text-decoration: underline;">Pseudocode</span> is an artificial and informal language that helps programmers develop algorithms. Pseudocode is a "text-based" detail (algorithmic) design tool.</p><p>The rules of Pseudocode are reasonably straightforward. All statements showing "dependency" are to be indented. These include while, do, for, if, switch. Examples below will illustrate this notion.</p><p><strong> GUIDE TO PSEUDOCODE LEVEL OF DETAIL: Given record/file descriptions, pseudocode should be created in sufficient detail so as to directly support the programming effort. It is the purpose of pseudocode to elaborate on the algorithmic detail and not just cite an abstraction. </strong></p><hr><p>Examples:</p><p>1.</p><pre>If student's grade is greater than or equal to 60
    Print "passed"
else
    Print "failed"  
endif
</pre><hr><p>2.</p><pre>  
Set total to zero
Set grade counter to one
While grade counter is less than or equal to ten
    Input the next grade
    Add the grade into the total
endwhile 
Set the class average to the total divided by ten
Print the class average.
</pre><hr><p>3.</p><pre>Initialize total to zero
Initialize counter to zero
Input the first grade
while the user has not as yet entered the sentinel
   add this grade into the running total 
   add one to the grade counter  
   input the next grade (possibly the sentinel)
endwhile

if the counter is not equal to zero
   set the average to the total divided by the counter
   print the average  
else
   print 'no grades were entered' 
endif 
</pre><hr><p>4.</p><pre>initialize passes to zero
initialize failures to zero
initialize student to one
while student counter is less than or equal to ten
    input the next exam result  
    if the student passed</pre><p>add one to passes else add one to failures add one to student counter endif endwhile print the number of passes print the number of failures if eight or more students passed print "raise tuition" endif</p><hr><h3><strong>5.</strong></h3><pre>Larger example:  

NOTE:  NEVER ANY DATA DECLARATIONS IN PSEUDOCODE

Print out appropriate heading and make it pretty
While not EOF do:
     Scan over blanks and white space until a char is found 
	(get first character on the line)
     set can't-be-ascending-flag to 0
     set consec cntr to 1
     set ascending cntr to 1
     putchar first char of string to screen
     set read character to hold character
     While next character read != blanks and white space
          putchar out on screen
          if new char = hold char + 1
               add 1 to consec cntr
               set hold char = new char
               continue
          endif
          if new char &gt;= hold char 
               if consec cntr &lt; 3 
                    set consec cntr to 1
               endif
               set hold char = new char
               continue
          endif
          if new char &lt; hold char
               if consec cntr &lt; 3
                    set consec cntr to 1
               endif
               set hold char = new char
               set can't be ascending flag to 1
               continue
           endif
     end while
     if consec cntr &gt;= 3 
          printf (Appropriate message 1 and skip a line)
          add 1 to consec total
     endif
     if  can't be ascending flag = 0
          printf (Appropriate message 2 and skip a line)
          add 1 to ascending total
     else
          printf (Sorry message and skip a line)
          add 1 to sorry total
     endif
end While
Print out totals:  Number of consecs, ascendings, and sorries.
Stop
</pre><p>Some Keywords That Should be Used And Additional Points</p><p>For looping and selection, The keywords that are to be used include Do While...EndDo; Do Until...Enddo; While .... Endwhile is acceptable. Also, Loop .... endloop is also VERY good and is language independent. Case...EndCase; If...Endif; Call ... with (parameters); Call; Return ....; Return; When;</p><p>Always use scope terminators for loops and iteration.</p><p>As verbs, use the words Generate, Compute, Process, etc. Words such as set, reset, increment, compute, calculate, add, sum, multiply, ... print, display, input, output, edit, test , etc. with careful indentation tend to foster desirable pseudocode. Also, using words such as Set and Initialize, when assigning values to variables is also desirable.</p><p>More on Formatting and Conventions in Pseudocoding</p><ul>
<li>INDENTATION in pseudocode should be identical to its implementation in a programming language. Try to indent at least four spaces.</li>
<li>As noted above, the pseudocode entries are to be cryptic, AND SHOULD NOT BE PROSE. NO SENTENCES.</li>
<li>No flower boxes (discussed ahead) in your pseudocode.</li>
<li>Do not include data declarations in your pseudocode.</li>
<li>But do cite variables that are initialized as part of their declarations. E.g. "initialize count to zero" is a good entry.<hr>Function Calls, Function Documentation, and Pseudocode</li>
<li>Calls to Functions should appear as:
<ul>     </ul>
</li>
<li>Returns in functions should appear as:
<ul> </ul>
</li>
<li>Function headers should appear as:
<ul>     </ul>
</li>
<li>Note that in C, arguments and parameters such as "fieldn" could be written: "pointer to fieldn ...."</li>
<li>Functions called with addresses should be written as:
<ul>         </ul>
</li>
<li>Function headers containing pointers should be indicated as:
<ul>        </ul>
</li>
<li>Returns in functions where a pointer is returned:
<ul>   </ul>
</li>
<li>It would not hurt the appearance of your pseudocode to draw a line or make your function header line "bold" in your pseudocode. Try to set off your functions.</li>
<li>Try to use scope terminators in your pseudocode and source code too. It really hels the readability of the text.<hr>Source Code</li>
<li>EVERY function should have a flowerbox PRECEDING IT. This flower box is to include the functions name, the main purpose of the function, parameters it is expecting (number and type), and the type of the data it returns. All of these listed items are to be on separate lines with spaces in between each explanatory item.</li>
<li>FORMAT of flowerbox should be
<p>&nbsp;</p>
<pre>	 ********************************************************
	 Function:   ( cryptic text describing single function
		     ....... (indented like this) 	
		     .......
	 Calls:      Start listing functions "this" function calls
		     Show these functions:  one per line, indented

	 Called by:  List of functions that calls "this" function
		     Show these functions:  one per line, indented.

	 Input Parameters:  list, if appropriate; else None
	 
	 Returns:    List, if appropriate.
	 ****************************************************************
</pre>
</li>
<li>INDENTATION is critically important in Source Code. Follow standard examples given in class. If in doubt, ASK. Always indent statements within IFs, FOR loops, WILLE loops, SWITCH statements, etc. a consistent number of spaces, such as four. Alternatively, use the tab key. One or two spaces is insufficient.</li>
<li>Use scope terminators at the end of if statements, for statements, while statements, and at the end of functions. It will make your program much more readable.
<p><strong> SPELLING ERRORS ARE NOT ACCEPTABLE </strong></p>
</li>
</ul>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

</channel>
</rss>