Data mining commonly involves four classes of tasks:

• Classification - Arranges the data into predefined groups. For example, an email program might attempt to classify an email as legitimate or spam. Common algorithms include decision tree learning, nearest neighbor, naive Bayesian classification and neural networks.
• Clustering - Is like classification but the groups are not predefined, so the algorithm will try to group similar items together.
• Regression - Attempts to find a function which models the data with the least error.
• Association rule learning - Searches for relationships between variables. For example a supermarket might gather data on customer purchasing habits. Using association rule learning, the supermarket can determine which products are frequently bought together and use this information for marketing purposes. This is sometimes referred to as market basket analysis.
• From experience, I can say that is one of the most frustrating positions to be in. Data mining is a huge field and can easily be bewildering for a beginner. However, high through-put techniques in molecular biology require, more and more, that bioinformatics is required to interpret the data. Furthermore, people working in bioinformatics generally come from computer science, or biology backgrounds. Data mining, however, involves statistics to one degree or another, which means entering a field that is may not be your strong point.
• Excel is fine for creating graphs. If you’re serious about data mining though, you’ll need something more heavy weight. I use R, free, and with good data mining packages such as vegan and labdsv. For beginners R can be impenetrable, I recommend this book an introduction to R as well as the underlying statistics.
• Any of us can rush head on into a land of support vector machines, hidden markov models and neural networks. But coming back to the first point, what are you trying to prove? Always question what are you doing, how does it fit in to the wider picture? Try to regularly review, and keep track of where you are going? This will prevent you from falling into data mining despair.

Data Mining Resources on the net:

A laboratory of data mining and bioinformatics is headed by Prof. Ambuj Singh. There are currently seven graduate students in the research group. Our research focuses on image informatics and scalable querying and mining of graphs.For more detail visit: http://www.cs.ucsb.edu/~dbl/

Here are the materials (Lecture notes) from several past courses on data mining and/or Web mining by Stanford: For detail visit: http://infolab.stanford.edu/~ullman/mining/mining.html
Statistical Data Mining Tutorial Slides by Andrew Moore The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. For detail visit: http://www.autonlab.org/tutorials/

A tutorial on Introduction to Data Mining for Discovering hidden value in your data warehouse:http://www.thearling.com/text/dmwhite/dmwhite.htm 
Wiki Links: http://en.wikipedia.org/wiki/Data_mining
Bioinformatics with Clementine http://www.spss.ch/upload/1051192224_inseratClemBio.pdf 
Causal Data Mining in Bioinformatics by Ioannis Tsamardinos: http://www.forth.gr/ics/bmi/In_the_News/2007/EN69-4.pdf

Report on ACM Text Mining in Bioinformatics (TMBIO 006) http://www.sigir.org/forum/2007J/2007j_sigirforum_song.pdf 
BIOKDD 2002: Recent Advances in Data Mining for 
Bioinformatics: http://www.acm.org/sigs/sigkdd/explorations/issue4-2/zaki.pdf

Bioinformatics and Medical Informatics: 

Tools for Mining and Applying Genetic Information in Patient Care:http://www.biomedtechalliance.org/pdfs/03_03_05/03_03_05.pdf

DATA MINING OF MICROARRAY DATABASES FOR HUMAN LUNG CANCER: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.106.385&rep=rep1&type=pdf

Towards knowledge-based gene expression data mining: http://www.ailab.si/blaz/papers/2007-JBI-BellazziZupan.pdf

DRAFT Accepted for publication in 'Data Mining in Bioinformatics'
Jason Wang, Mohammed Zaki, Hannu Toivonen, and Dennis Shasha (Eds.), Springer:http://www.cs.helsinki.fi/u/htoivone/pubs/gene_mapping_by_pattern_discovery.pdf

Data Mining and Text Mining for Bioinformatics: Proceedings of the European Workshop: http://www.rok.informatik.hu-berlin.de/wbi/research/publications/2003/proceedings_ws_mining.pdf

Biological Network Analysis:

Graph Mining in Bioinformatics: http://agbs.kyb.tuebingen.mpg.de/wikis/bg/BNA-5.pdf.

Text mining in bioinformatics: http://agbs.kyb.tuebingen.mpg.de/wikis/bg/4.pdf

Some datamining books that are available on google books:

Data mining and bioinformatics: first international workshop, VDMB 2006 By Mehmet M. Dalkilic

Data mining: concepts and techniques By Jiawei Han, Micheline Kamber

1. TATA SCHOLARSHIP - Cornell University, New York State, USA
Tata, the Indian multinational conglomerate company, have a foundation known as the Tata Education & Development Trust which has endowed a multi million dollar sum to Cornell University to provide undergraduate scholarships to 20 Indian students every year.  In another example of supporting American universities, the Tata group also pledged US$50 million to Harvard University in recent years, whose executive management programme Ratan Tata attended in the 1970s.  Read more...  

2. BRADMAN FOUNDATION SCHOLARSHIP - University of Wollongong, Australia.
Named after Australia's cricket legend Donald Bradman, the UOW Bradman Foundation Scholarship was launched in 2012, with the help of Adam Gilchrist no less, to offer one successful Indian student each year a 50% reduction in tuition fees.  Read more...  

3. HUAWEI MAITREE SCHOLARSHIPS - Various Universities, China
Along with Tata, Huawei are the other huge corporation to be featured.  China's massive telecoms equipment vendor are involved in these scholarships offered to Indian students studying in China.  In 2013 there are 10 generous scholarships available which provide full tuition fees and living expenses.  The courses on which the scholarships are offered include Science and Technology courses, Social Sciences and Culture and Development courses.  Read more...

4. DR. MANMOHAN SINGH SCHOLARSHIPS - Cambridge University, England, UK
These scholarships have been designed to help budding Indian minds follow in the footsteps of Indian prime minister Manmohan Singh by studying at the prestigious Cambridge University.  The scholarships can be applied to any undergarduate course (with the two exceptions of medicine and veterinary science) and cover everything, i.e. tuition and college fees, living expenses and an additional grant to go towards travel expenses.  Read more...

5. OXFORD AND CAMBRIDGE SOCIETY OF INDIA - Oxford & Cambridge Universities, England, UK
As the name might suggest, these are scholarships available for students wishing to study at Oxford or Cambridge (cleverly known together as Oxbridge).  It is only available for applicants who are completing or have completed a degree at an Indian university, however these scholarships are for both undergraduate and graduate students.  Read more...

6. EDINBURGH NAPIER UNIVERSITY - Scotland, UK
This one applies to all countries in the Indian subcontinent and is for both undergraduate and graduate courses. Edinburgh Napier University offers a merit based discount of £2,000 Pounds.  Read more...

7. SHEFFIELD UNIVERSITY - Sheffield, UK
Provides merit-based scholarships for undergraduate and graduate programmes across all subjects. Read more...

8. INDIA 4EU II - Several Universities across Europe
Pioneered by the European Union and involving partner universities in France, Finland, Germany, Italy, Portugal, Spain and Sweden, the India 4EU II initiative is aimed at encouraging Indian students to study, work and live in Europe.  The initiative is well funded and allows the successful students tuition fees, expenses for living and travel costs as well as insurance during their time at one of the partner universities.  Read more...

9. TRINITY COLLEGE DUBLIN - Ireland
Valid for undergraduate courses in the faculties of Arts, Humanities, Social Sciences, Science, Computer Science or Engineering, the Trinity College Dublin offers Indian students scholarships to the tune of €9,000 per annum over a year degree course.  Read more...

10. UNIVERSITY COLLEGE DUBLIN - Ireland
Another of Ireland and Dublin's finest, the UCD awards one Global Excellence Undergraduate Scholarship which provides the worthy student a substantial 50% towards their tuition fees and is valid for all courses save medicine, radiography and veterinary medicine.  UCD also offers a Global Undergraduate Scholarship scheme for undergrads accepted on science, social sciences, arts and business courses.  This is all thanks to a €250,000 fund that will allow for 57 Indian students to benefit from scholarships at UCD.  Read more...

Research with the help of bioinformatics with a trans-disciplinary approach is yielding good results.

http://www.thehindu.com/features/education/research/research-with-help-of-bioinformatics-helpful/article2295629.ece

The most common newbie questions are:

Should I try to use these free open source programs?  Why are we not trying GUI software for computational analysis? Should I use commercial bioinformatics programs/software?”

1. Let’s be open

We generally think free and cheap are useless. But this concept is not applicable when we discuss open source software. Mostly, the bioinformatics software is developed by highly competitive biological programmers who believe in open sharing of knowledge. They come under Open Bioinformatics Foundation or O|B|F which is a non-profit, volunteer run organization focused on supporting open source programming in bioinformatics. The best part about open source tools/software is that they’re free to download the source code and read exactly what the program does. If you are so inclined, you can view all of the parts of the program and see the logical flow of the pipeline. In addition, open source makes an excellent learning tool for any beginning bioinformatician. Moreover, you can modify existing open source programs to deal with cutting-edge problems or to customize your pipeline. Apart from your computational and analysis work, most of the reviewer also prefers the open source based results so that they can validate the results if validation required.

2. Code headache

As a bioinformatician you are supposed to know the basics of programming languages, and if you are not good at it, then please learn it as soon as possible because you are not a bio-analyst but biological programmers. The open source programs usually lack dedicated service and support teams (often because they were the product of an overworked doc/postdoc!) so you are responsible for troubleshooting your own errors most of the time. We commonly receive the HELP email to support and assist to setup the pipeline; you can also find this kind of request on any QA forum. I personally believe this coding horror brings the biggest downside of open-source programs; where you need some programming skills in order to implement the program in your pipeline. But, if you are not able to fix the pipeline and modify the open source code according to your requirements them you should re-think on your bioinformatician name tag!!!

3. Dive into the codes

Some of the biologist turn bioinformatician says “if you can do the same thing with commercial software then why to get migraine with weird codes”, well this statement looks to me that guys are keen to learn swimming but still don’t like to get wet. If you are still using paid software and doing your work by customer support and clicking some of the well-designed GUI button then perhaps you are not interested in learning and trying new and challenging bioinformatics works. You are missing the basic flavour of bioinformatics. Let’s dive into the coding world, I am sure your will enjoy it. I recommend your to swim freely in code’s sea, and enjoy the journey; do not merely watch it from the outside.  

4. Paid does not mean better

The bioinformatics company which are specializes in bioinformatics solutions develop well designed/packed, user friendly software by using a large number of specialised scientist, programmers and support staff. They also provide good services to accomplice your biological analysis work. This means that if you hit a ‘snag’ with your data, help is likely only a phone call away! These companies price their products competitively against the cost of a dedicated bioinformatician. You may be able to afford the program, but not the additional staff! Additionally, most of the functionality that you need in your analysis is already coded into the program. Need to plot a graph? Just click this button right here. It is that easy. But, as a bioinformatician this is not generally well encouraged approach in biological analysis work, because the software is not available to everyone and your data can’t be validated. Moreover, there is very less chances that anyone will repeat your work or love to do similar kind of research (because not all the labs in the world are rich like yours).

5. Take a caution

In biological analysis work, in which you deal GB/TB of data are having maximum chances of getting errors, so please be careful and always cross check your data before coming to any conclusion. Even an error in two line code can alter your entire analysis and display weird results. Some of the scientist blindly believes on commercial software, which is entirely wrong. Using proprietary tools does not absolve you of the need to actually read and research the type of analysis that you are doing. This is particularly true in the case of genome assembly and annotation.

At the end, I would like to tell only one think that open source solutions allows you to do more cutting edge analysis than the commercial tools. So let’s go for it.

Disclaimer:

This is my personal view. I have nothing to do with any company or open source community. The views expressed on these pages are mine alone and not those of my current/past employers. I do reserve the right to remove comments left by spammers or off-topic comments.

Address of the bookmark: https://www.igenbio.com/ergo/

Perl's second wave of adoption came from the growth of the world wide web. Dynamic web pages—the precursor to modern web applications—were easy to create with Perl and CGI. Thanks to Perl's ubiquity as a language for system administrators and its power to manipulate text, it was the default choice for web programming. Its presence everywhere made it popular and, in some ways, the duct tape of the Internet.

Web Application Development

The old days of CGI programs and the simple development style that represented seem clunky. Web pages have become web applications. Development has moved from generating static HTML to both client and server side programming, with rich client interfaces and powerful backends.

Perl is still well suited for developing modern web apps. The language grows more powerful and easier to use every year, the available libraries are wonderful and keep getting better, and the inventions and discoveries available in modern Perl are unsurpassed.

In particular, a modern Perl developer can do amazing things with modern Perl tools. If you still think of Perl web development as a cgi-bin directory full of messy scripts that spew warnings to STDERR, you're a decade out of date. Better yet, you can replace that mess piecemeal, thanks to the new tools and techniques of modern Perl. See, for example, the ever-growing list of technologies Built in Perl.

Modern Perl Web Frameworks

While the old wave of web development may have made the CGI.pm module central, modern Perl web programming follows a stricter separation of business logic, URL and request routing, and output. The days of slinging a string here, an array there, a Perl hash yonder, declaring every variable at the top of the program, and maybe making a subroutine are gone. The Perl world has seen the value of abstraction and ways to mechanize away boilerplate. Perl has dozens of frameworks and toolkits designed to make web development and deployment simpler.

Any of a dozen of these frameworks will help you do great things, but three in particular stand out. You can build web sites and web applications of tremendous value with all three. These are neither the only good possibilities (think of POE or Jifty or Continuity or...) nor the only mechanisms for web programming with Perl (see Mechanize or LWP or Mojo::UserAgent for more). Yet if you want three good options to choose between, start here.

Catalyst

The Catalyst framework is a flexible and powerful system for building small to large web apps. It uses the Moose object system to provide great APIs for extension and further development. It's the most mature of the modern top Perl web frameworks, yet it retains its flexibility and vibrancy. In particular, its plugin and extension ecosystem allows it to evolve to provide new and essential features.

Catalyst has embraced the Plack/PSGI standard for Perl web deployment and recent versions are exploring high-scalability, event-based request handling models.

Dancer

The Dancer framework is deliberately minimal in syntax and scope, but it also has a vibrant plugin ecosystem. Dancer particularly excels for smaller sites and applications, though good programmers can build larger things with it.

The first version of Dancer was easy to use. Dancer 2 continues that ease while improving the internals and robustness of applications.

Mojolicious

The Mojolicious (Mojo) framework has a real-time design based on high performance event handling. Its focus is solving new and interesting problems in simple and effective ways, and the project has produced a lot of new code that does old things in better ways.

In particular, Mojolicious goes to great lengths to support new web standards, such as CSS 3, web sockets, and HTTP 2.

Where Catalyst embraces the CPAN fully, Mojolicious by design provides most of what an average app might need in a single download. It's still fully compatible with the CPAN, but the intention is to provide good working defaults in a package that's easy to start with. Mojo's fans are quick to praise it as fun to develop.

A modern Perl web developer should be familiar with at least one of these frameworks.

Modern Perl Storage Mechanisms

Perl's venerable DBI module has been the focal point of database access since its invention. Its design allows it to provide the same interface to huge relational databases and flat files alike through its DBD extension mechanism. Yet the DBI by itself isn't the be-all, end-all of data storage and access in Perl.

DBIx::Class

DBIx::Class sits on top of DBI to provide an API to your database based on the concept of queries and results. This is often sufficient to remove all but the most complicated of SQL from your code, leaving you to manipulate your business models instead of the small details of how a relational database works. The power and maintainability you receive is well the small cost of the learning curve.

Even better, DBIC can manage (and even generate) your database schema for you.

Recent versions of DBIC have demonstrated that a well-written ORM can perform much better than even clever hand-written code. Because it builds on the Perl DBI, it scales everywhere from SQLite to PostgreSQL, MySQL, Oracle, and more.

Rose::DB

The lesser-known but no less powerful Rose::DB::Object builds on Rose::DB to provide an object-relational mapper for Perl. While its high level features most directly compare to those of DBIx::Class, it's often measurably faster.

NoSQL on the CPAN

Of course the CPAN has modules for almost any NoSQL database or job queue or persistence mechanism you could name, and several you have never heard of. Everything you need is a quick CPAN or cpanm away!

Modern Perl Deployment Strategies

In the early days of the web, deploying a Perl web application meant putting one or more .cgi or .pl files in a special directory and hoping that your system administrator had everything configured correctly. The execution model was often slow and cumbersome, and accessing shared resources such as databases was often tricky.

Modern Perl has better choices. While deployment strategies are the source of many arguments, the return on your investment from learning the modern way is impressive.

Plack/PSGI

The PSGI specification (as exemplified by Plack) describes a strategy for building Perl web apps independent of server and with the possibility to share custom processing behaviors.

In other words, it's a standard for writing Perl apps to take advantage of the huge ecosystem of Perl development available on the CPAN without tying yourself to a server like Apache, Apache 2, nginx, or anything else.

Any good modern Perl web framework (including those listed here) supports PSGI. Several deployment mechanisms exist to meet various business needs which also support PSGI. In particular, you can deploy the same application with a local testing server on your own machine as you can to your production server or servers without changing your application at all.

mod_perl

The older but still viable mod_perl Apache httpd module embeds Perl into the web server. This was the first widespread persistence mechanism for Perl web applications themselves and it's still popular to this day, though PSGI compliance is often the choice for new development. (PSGI handlers to use mod_perl as the backend are available.)

Modern Perl developers should familiarize themselves with PSGI and the wealth of available Plack middleware.

Perl Web Development

Of course no discussion of Perl web development would be complete without mentioning the strength of the CPAN. Almost any project will benefit from the wealth of freely available libraries built to solve real problems. These distributions run the gamut from full-blown web frameworks and content management systems to APIs for web services, development tools, testing systems, and interfaces to document formats and external resources.

For example, if you need to write a web service which accepts JSON data and produces Excel spreadsheets, you can glue together a few CPAN distributions and get the job done early. If you need to consume XML from a remote service and emit a PDF, you're in luck.

Perl's prowess as a general purpose programming language as well as its flexibility and power in managing text and gluing systems together make it a wonderful fit for web development. The community's adoption of modern Perl standards such as PSGI and Plack only enhance your power.

Web application development in Perl is still viable, and modern Perl tools and techniques and libraries make it more powerful and pleasant than ever.

• File System
  ls — list items in current directory
  ls -l — list items in current directory and show in long format to see perimissions, size, and modification date
  ls -a — list all items in current directory, including hidden files
  ls -F — list all items in current directory and show directories with a slash and executables with a star
  ls dir — list all items in directory dir
  cd dir — change directory to dir
  cd .. — go up one directory
  cd / — go to the root directory
  cd ~ — go to to your home directory
  cd - — go to the last directory you were just in
  pwd — show present working directory
  mkdir dir — make directory dir
  rm file — remove file
  rm -r dir — remove directory dir recursively
  cp file1 file2 — copy file1 to file2
  cp -r dir1 dir2 — copy directory dir1 to dir2 recursively
  mv file1 file2 — move (rename) file1 to file2
  ln -s file link — create symbolic link to file
  touch file — create or update file
  cat file — output the contents of file
  less file — view file with page navigation
  head file — output the first 10 lines of file
  tail file — output the last 10 lines of file
  tail -f file — output the contents of file as it grows, starting with the last 10 lines
  vim file — edit file
  alias name 'command' — create an alias for a command
  
• System
  shutdown — shut down machine
  reboot — restart machine
  date — show the current date and time
  whoami — who you are logged in as
  finger user — display information about user
  man command — show the manual for command
  df — show disk usage
  du — show directory space usage
  free — show memory and swap usage
  whereis app — show possible locations of app
  which app — show which app will be run by default
  
• Process Management
  ps — display your currently active processes
  top — display all running processes
  kill pid — kill process id pid
  kill -9 pid — force kill process id pid
  
• Permissions
  ls -l — list items in current directory and show permissions
  chmod ugo file — change permissions of file to ugo - u is the user's permissions, g is the group's permissions, and o is everyone else's permissions. The values of u, g, and o can be any number between 0 and 7.
  7 — full permissions
  6 — read and write only
  5 — read and execute only
  4 — read only
  3 — write and execute only
  2 — write only
  1 — execute only
  0 — no permissions
  chmod 600 file — you can read and write - good for files
  chmod 700 file — you can read, write, and execute - good for scripts
  chmod 644 file — you can read and write, and everyone else can only read - good for web pages
  chmod 755 file — you can read, write, and execute, and everyone else can read and execute - good for programs that you want to share
  
• Networking
  wget file — download a file
  curl file — download a file
  scp user@host:file dir — secure copy a file from remote server to the dir directory on your machine
  scp file user@host:dir — secure copy a file from your machine to the dir directory on a remote server
  scp -r user@host:dir dir — secure copy the directory dir from remote server to the directory dir on your machine
  ssh user@host — connect to host as user
  ssh -p port user@host — connect to host on port as user
  ssh-copy-id user@host — add your key to host for user to enable a keyed or passwordless login
  ping host — ping host and output results
  whois domain — get information for domain
  dig domain — get DNS information for domain
  dig -x host — reverse lookup host
  lsof -i tcp:1337 — list all processes running on port 1337
  
• Searching
  grep pattern files — search for pattern in files
  grep -r pattern dir — search recursively for pattern in dir
  grep -rn pattern dir — search recursively for pattern in dir and show the line number found
  grep -r pattern dir --include='*.ext — search recursively for pattern in dir and only search in files with .ext extension
  command | grep pattern — search for pattern in the output of command
  find file — find all instances of file in real system
  locate file — find all instances of file using indexed database built from the updatedb command. Much faster than find
  sed -i 's/day/night/g' file — find all occurrences of day in a file and replace them with night - s means substitude and g means global - sed also supports regular expressions
  
• Compression
  tar cf file.tar files — create a tar named file.tar containing files
  tar xf file.tar — extract the files from file.tar
  tar czf file.tar.gz files — create a tar with Gzip compression
  tar xzf file.tar.gz — extract a tar using Gzip
  gzip file — compresses file and renames it to file.gz
  gzip -d file.gz — decompresses file.gz back to file
  
• Shortcuts
  ctrl+a — move cursor to beginning of line
  ctrl+f — move cursor to end of line
  alt+f — move cursor forward 1 word
  alt+b — move cursor backward 1 word
  

https://academic.oup.com/bioinformatics/article/30/18/2559/2475628
Reference-free SNP detection: dealing with the data deluge

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083407/
GATB/DiscoSnp: DiscoSnp is designed for discovering all kinds of SNPs (not only isolated ones), as well as insertions and deletions, from raw set(s) of reads.

https://github.com/GATB/DiscoSnp
De novo assembly | Oxford Nanopore Technologies

https://nanoporetech.com/taxonomy/term/131
De novo long-read assembly of a complex animal genome | bioRxiv

https://www.biorxiv.org/content/early/2017/09/10/187054
Rapid de novo assembly of the European eel genome from nanopore sequencing reads | Scientific Reports

https://www.nature.com/articles/s41598-017-07650-6.epdf?author_access_token=dktG7e98wyRJnaEEMTcPqtRgN0jAjWel9jnR3ZoTv0P7E7t-wVGo30iojNO7dICajNY_7PE5xVPv6OoLe7hn9TeUjcZ5umREOzNoPMWkfYH58RS6uxm3vm4e4BG2AA_WKW84i6egKK271NwMq-NfzA%3D%3D
nanoporetech/ont-assembly-polish: ONT assembly and Illumina polishing pipeline

https://github.com/nanoporetech/ont-assembly-polish
Generade-nl/TULIP: TULIP - The Uncorrected Long read Itegration Pipeline

https://github.com/Generade-nl/TULIP
www.nature.com

https://www.nature.com/articles/s41598-017-03996-z
Example gallery of NanoPlot – Gigabase or gigabyte

https://gigabaseorgigabyte.wordpress.com/2017/06/01/example-gallery-of-nanoplot/
Tool documentation

https://broadinstitute.github.io/picard/command-line-overview.html
Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. - PubMed - NCBI

https://www.ncbi.nlm.nih.gov/pubmed/24185095
MAFFT ver.7 - a multiple sequence alignment program

https://mafft.cbrc.jp/alignment/software/algorithms/algorithms.html
Measuring the distance between multiple sequence alignments | Bioinformatics | Oxford Academic

https://academic.oup.com/bioinformatics/article/28/4/495/212883
The MUMmer 3 examples

http://mummer.sourceforge.net/examples/
MAFFT ver.7 - a multiple sequence alignment program

https://mafft.cbrc.jp/alignment/software/tips.html
Omega | Overlap-graph de novo Assembler for Metagenomics

https://omega.omicsbio.org/
abiswas-odu/Disco: Multi-threaded Distributed Memory Overlap-Layout-Consensus (OLC) Metagenome Assembler

https://github.com/abiswas-odu/Disco
SAGE: String-overlap Assembly of GEnomes | BMC Bioinformatics | Full Text

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-302

Fast and sensitive mapping of nanopore sequencing reads with GraphMap | Nature Communications

https://www.nature.com/articles/ncomms11307
lumpy-sv/extractSplitReads_BwaMem at master · arq5x/lumpy-sv

https://github.com/arq5x/lumpy-sv/blob/master/scripts/extractSplitReads_BwaMem
jts/nanocorrect: Experimental pipeline for correcting nanopore reads

https://github.com/jts/nanocorrect

video - how to install flash plugin on ubuntu 14.04 LTS 64-bit version - Ask Ubuntu

https://askubuntu.com/questions/469553/how-to-install-flash-plugin-on-ubuntu-14-04-lts-64-bit-version
lh3/fermi: A WGS de novo assembler based on the FMD-index for large genomes

https://github.com/lh3/fermi
Multi-metagenome

http://madsalbertsen.github.io/multi-metagenome/docs/step9.html
Bandage by rrwick

https://rrwick.github.io/Bandage/
Codon Optimization OnLine (COOL): a web-based multi-objective optimization platform for synthetic gene design | Bioinformatics | Oxford Academic

https://academic.oup.com/bioinformatics/article/30/15/2210/2391162
Genome Architecture and Evolution of a Unichromosomal Asexual Nematode - ScienceDirect

https://www.sciencedirect.com/science/article/pii/S096098221731076X?via%3Dihub#fig4
How to determine chimeras in my de novo assembly? - SEQanswers

http://seqanswers.com/forums/showthread.php?t=26721
samtools(1) manual page

http://www.htslib.org/doc/samtools.html
How To Filter Mapped Reads With Samtools

https://www.biostars.org/p/56246/
The MUMmer 3 manual

http://mummer.sourceforge.net/manual/#nucmer
assembly_olc.pdf

http://www.cs.jhu.edu/~langmea/resources/lecture_notes/assembly_olc.pdf
SAM and BAM filtering oneliners

https://gist.github.com/davfre/8596159
Inroduction to dot-plots

http://www.code10.info/index.php%3Foption%3Dcom_content%26view%3Darticle%26id%3D64:inroduction-to-dot-plots%26catid%3D52:cat_coding_algorithms_dot-plots%26Itemid%3D76
RepeatFinder Home Page

http://www.cbcb.umd.edu/software/RepeatFinder/
RepeatFinderReprint.pdf

http://www.cbcb.umd.edu/software/RepeatFinder/RepeatFinderReprint.pdf
https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CreateIdeogram/CreateIdeogram.html

https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CreateIdeogram/CreateIdeogram.html
Circular Visualization in R

http://zuguang.de/circlize_book/book/introduction.html#a-qiuck-glance
Creating a coverage plot using BEDTools and R

https://davetang.org/muse/2015/08/05/creating-a-coverage-plot-using-bedtools-and-r/
Eval: A software package for analysis of genome annotations | BMC Bioinformatics | Full Text

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-4-50
eval-documentation.pdf

http://mblab.wustl.edu/media/software/eval-documentation.pdf
OmicCircos: A Simple-to-Use R Package for the Circular Visualization of Multidimensional Omics Data

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3921174/
sequence - download.tardigrades.org > v1 > sequence

http://download.tardigrades.org/v1/sequence/
ksahlin/BESST: BESST - scaffolder for genomic assemblies

https://github.com/ksahlin/BESST
reubwn/scripts: Useful scripts for various things

https://github.com/reubwn/scripts
ICEberg

http://db-mml.sjtu.edu.cn/ICEberg/index.php
Satsuma - Evolution and Genomics

http://evomics.org/learning/genomics/satsuma/
A complete bacterial genome assembled de novo using only nanopore sequencing data | Nature Methods

https://www.nature.com/articles/nmeth.3444
vezzi/FRC_align: Computes FRC from SAM/BAM file and not from afg files

https://mail.google.com/mail/u/0/#inbox
Read GTF file into R - Dave Tang's blog

https://davetang.org/muse/2017/08/04/read-gtf-file-r/

https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CustomGenomes/CustomGenomes.html

https://bernatgel.github.io/karyoploter_tutorial//Tutorial/CustomGenomes/CustomGenomes.html
Dot: Interactive dot plot for genome-genome alignments

https://dnanexus.github.io/dot/
Zoho Accounts

https://accounts.zoho.eu/signin?servicename=ZohoProjects&serviceurl=https%3A%2F%2Fprojects.zoho.eu%2Fportal%2Favaga2
lh3/minimap2: A versatile pairwise aligner for genomic and spliced nucleotide sequences

https://github.com/lh3/minimap2
SSPACE-LongRead: scaffolding bacterial draft genomes using long read sequence information | BMC Bioinformatics | Full Text

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-211
Palindromic gene amplification — an evolutionarily conserved role for DNA inverted repeats in the genome | Nature Reviews Cancer

https://www.nature.com/articles/nrc2591
bioinformatics - BLAST DNA Sequences Reversed - Biology Stack Exchange

https://biology.stackexchange.com/questions/8160/blast-dna-sequences-reversed
LASTZ

http://www.bx.psu.edu/miller_lab/dist/README.lastz-1.02.00/README.lastz-1.02.00a.html
SOGo - (1652) Inbox

https://sogo.unamur.be/SOGo/so/jnarayan/Mail/view
Tetra-Nucleotide Analysis (TNA) | BIOiPLUG Help center

http://help.bioiplug.com/tetra-nucleotide-analysis-tna/

Clustering metagenomic contigs on tetranucleotide frequency — CGAT documentation

http://cgat.readthedocs.io/en/latest/recipes/metagenome_contigs_kmers.html