Address of the bookmark: http://engr.case.edu/li_jing/papers/00798gpattern.pdf

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.

Pseudocode is an artificial and informal language that helps programmers develop algorithms. Pseudocode is a "text-based" detail (algorithmic) design tool.

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.

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.

Examples:

1.

If student's grade is greater than or equal to 60
    Print "passed"
else
    Print "failed"  
endif

2.

  
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.

3.

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 

4.

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

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

5.

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 >= hold char 
               if consec cntr < 3 
                    set consec cntr to 1
               endif
               set hold char = new char
               continue
          endif
          if new char < hold char
               if consec cntr < 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 >= 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

Some Keywords That Should be Used And Additional Points

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;

Always use scope terminators for loops and iteration.

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.

More on Formatting and Conventions in Pseudocoding

• INDENTATION in pseudocode should be identical to its implementation in a programming language. Try to indent at least four spaces.
• As noted above, the pseudocode entries are to be cryptic, AND SHOULD NOT BE PROSE. NO SENTENCES.
• No flower boxes (discussed ahead) in your pseudocode.
• Do not include data declarations in your pseudocode.
• But do cite variables that are initialized as part of their declarations. E.g. "initialize count to zero" is a good entry.

  ---

  Function Calls, Function Documentation, and Pseudocode
• Calls to Functions should appear as:
• Returns in functions should appear as:
• Function headers should appear as:
• Note that in C, arguments and parameters such as "fieldn" could be written: "pointer to fieldn ...."
• Functions called with addresses should be written as:
• Function headers containing pointers should be indicated as:
• Returns in functions where a pointer is returned:
• 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.
• Try to use scope terminators in your pseudocode and source code too. It really hels the readability of the text.

  ---

  Source Code
• 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.
• FORMAT of flowerbox should be

   

  	 ********************************************************
  	 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.
  	 ****************************************************************
  

• 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.
• 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.

  SPELLING ERRORS ARE NOT ACCEPTABLE

Many times in bioinformatics we need to deal with huge datasets which  are more than 100GB size. The traditional way to analysis a file is using the while loop

while (FILE){

Do something;

}

This is very slow(since we are using only one processor) and if we have 500 million lines in the dataset it takes more than a day to iterate through the whole dataset. So how do we make best use of all our processors and get the work done quickly?

Here is a very simple and efficient technique with perl which i have been using. I am  more inclined towards using perl fork than perl threads.

One of the oldest way to fork is

my $fork = fork();
if($fork){   
push (@childs,$fork); 
}
elseif($fork==0){
your code here;
exit(0);
}
else{die “Couldnt fork : $!”;}

## wait for the child process to finish
foreach(@childs){
my $tmp=waitid($_,0);
}

what a fork does is it creates a child process and takes the variables and code with it to analyze it separately (detached from the parent process) and thus a separate process is created( which usually runs on a separate processor). Thats it!! One big disadvantage of forking is its very difficult to share variables among the different processes. I will show you how to do it easily but still it has its own drawbacks.

Okie, now if you really do not want to use fork in your code, that’s okie too..There are many useful modules which do it for you very efficiently. One really useful module is Parallel::ForkManager. You can use Parallel::ForkManager to manage the number of forks you want to generate (number of processors you want to use).

Simple usage:
use Parallel::ForkManager;
my $max_processors=8;
my $fork= new Parallel::ForkManager($max_processors);
foreach (@dna) {
$fork->start and next; # do the fork
you code here;
$fork->finish; # do the exit in the child process
}
$pm->wait_all_children;

so you will be generating 8 forks which do the same thing for your each element of array. when one child finishes, Parallel::ForkManager generates a new one and thus you will be using all your processors to analyze the data. Now, if you have generated 8 child processes and want to write the data to one file. You need to lock the file to do this, because you will have problems with the buffering. You can lock the file using flock command.

open (my $QUAL, “myfile.txt”);
flock $QUAL, LOCK_EX or die “cant lock file $!”;
print $QUAL “$output”;
flock $QUAL, LOCK_UN or die “$!”;
close $QUAL;

I would not suggest using flock when dealing with multiple processes because it will decrease the processing efficiency( each child process must wait for the lock to be released by the other child process). Instead, I would suggest each fork writing to a separate file and after the processing just concatenating them.

Putting it all together, If you have 100GB data you can do this

step 1 : split the dataset equally according to number of processors you have. this may take a few hours(about 2-3 hrs for 100GB file)
You can use unix “split” command for this
for example:
my $number_split=int($number_of_entries_in_your_dataset/$max_processors);
my $split_Files=`split -l $number_split “your_file.fasta” “file_name”`;

step2: open you directory comtaining you split files and start Parallel::ForkManager.
For example:
opendir(DIRECTORY, $split_files_directory) or die $!; ### open the directory
my $fork= new Parallel::ForkManager($max_processors);
while (my $file = readdir(DIRECTORY)) { ### read the directory
if($file=~/^\./){next;}
print $file,”\n”;
########## Start fork ##########
my $pid= $super_fork->start and next;
Whatever you want to do with the split file ;
analyze my piece of $file;
######### end fork ###############
$super_fork->finish;
}
$super_fork->wait_all_children;

So basically each processor will be active with its piece of data (split file) and thus you have created 8 processes at one time which run without interfering with the other process. I again will not suggest writing output from each child process to one file(for reasons above). Write output from each fork to a separate file and finally concatenate them. Thats it, you have just increased your program speed by 8 times!! Isnt it easy?

Note:
You may worry about concatenation of the output each child generates, since it does take some time(remember 100GB). I think now you can use a mysql database LOAD DATA LOCAL INFILE command to load all the files into a single table(Should take about 3hrs for 100Gb dataset) and then export the whole table into one file. This should be faster than just concatenating them using “cat” command.(correct me if I am wrong)

Or much simpler way is to use pipes

cat output_dir/* | my_pipe or my_pipe <(file1) final_file;

Thats it guys!! Enjoy programming and please do comment. I am not a computer scientist so forgive me for any mistakes and if any please report them. Thank you.

Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.

Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.

Desirable Qualifications (Research Associate/s): i) Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment).

ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv) Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.

The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.

Emoluments: As per DST, GOI norms and commensurate with experience.

More at https://www.iisc.ac.in/positions-open/

Research Interest and Activities: 1. Plant Genetic Transformations
2. Molecular Population Genetics 3. Detection of human and Animals diseases 4. Breast Cancer­specific protein marker 5. Phytochemical 6. Genomic map 7. Bioremediation 8. Tissue Culture.

Web site and links: www.geocity.cbge.com

https://bioinformaticsworkbook.org/

Address of the bookmark: https://bioinformaticsworkbook.org/

https://bioinformatics.kmutt.ac.th/about.html

Duangrudee Tanramluk (Ajarn Wi) uses computational biology and machine learning to tackle the key to drug design problems via MANORAA webserver.

https://mb.mahidol.ac.th/en/bioinformatics/

https://graduate.mahidol.ac.th/inter/

This international Doctorate programme is designed to further broaden students’ knowledge in Bioinformatics and Molecular Biology to their maximum capability. 

http://www.mbb.psu.ac.th/programmes/phd

Ph.D. program in Bioinformatics and Computational Biology is a joint effort of the Faculty of Science and Faculty of Medicine, Chulalongkorn University. The program has study plans for both applicants who hold a bachelor’s degree and applicants who hold a master’s degree in any related fields of study.

http://www.bioinfo.sc.chula.ac.th/ph-d-program-specialization/

Additional detail 

https://www.biotec.or.th/en/index.php/research/research-units/genome-technology-research-unit

https://tbrcnetwork.org/labtbrc/index.php/bioinformatics-and-chemoinformatics/

https://genomicsthailand.com/Genomic/home

Address of the bookmark: https://bioinformatics.kmutt.ac.th/

Since this is your first time here, I suggest starting with something simple like Fizz Buzz.

Address of the bookmark: https://code.golf/

People say that interviews at Google will cover as much ground as possible. As a new college graduate, the ground that I must capture are the following. Part of the list is borrowed from a reddit post: https://www. reddit.com/r/cscareerquestions/comments/206ajq/my_onsite_interview_experience_at_google/ #bottom-comments.

1. Data structures

2. Trees and Graph algorithms

3. Dynamic Programming

4. Recursive algorithms

5. Scheduling algorithms (Greedy)

6. Caching 1

7. Sorting

8. Files

9. Computability

10. Bitwise operators

11. System design