It was originally developed at the Wellcome Trust Sanger Institute to bundle a FASTA sequence and its quality data, but has recently become the de facto standard for storing the output of high-throughput sequencing instruments such as the Illumina Genome Analyzer.^[1]

Address of the bookmark: https://en.wikipedia.org/wiki/FASTQ_format

https://bienkocrosettolabs.org/

Dr Altan Kara is a Bioinformatics specialist at the faculty of Gene Engineering and Biotechnology Institute at TUBITAK MAM Research Center. His research interest revolves around the cancer informatics and computational aided-drug design. I applaud Dr Altan for clearly setting out both his expectations of people that join his lab/university in addition to listing his responsibilities to his research members at TUBITAK MAM Research Institüte. Hopefully, this interview will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.

You can find out more about Dr Altan by visiting his (well documented) lab page (http://gmbe.mam.tubitak.gov.tr/en) and BOL page http://bioinformaticsonline.com/profile/altan . And now, on to the BOL:“Tryst with a Bioinformatician” interview series ...

• What push you to join Computational Biology/Bioinformatics?

According to me, bioinformatics is the center of modern biological research and if a researcher wants to discover new biological insights by evaluating the globally produced biological data to derivate unified solutions for specific biological problems, learning bioinformatics is the only way to achieve this goal.

• What fascinates you about Computational Biology/Bioinformatics?

It's flexibility. As well known, there are highly diverse and complex biological questions are waiting to be enlightened and it's impossible to bring solutions to this diversity by using similar approaches. Thus, the employed method has to be unique for the targeted biological problem and by using bioinformatics tools this can be easily achieved. 

• What is the one word you would use to describe yourself?

Bioinformatician. :)

• Can you please describe your research work in a nutshell for BOL users.

At my current Institute, I am working in the field of cancer bioinformatics. Briefly, the overall aim of the project which I am working for (AKMARK (Project CODE:5153403)) is, applying a bioinformatics-supported genome, transcriptome, proteome, and metabolome analysis to reveal the molecular profile of the disease through an integrated approach, and to develop an early diagnosis and scanning kit based on this profile. Alterations in the gene, transcript, protein, and metabolite profiles between normal tissue, normal tissue adjoined to the tumor (reactive stroma), tumor tissue, lymph node metastasis, and blood samples taken from the same patient and the reflection of these changes in some other selected body fluids will be revealed within the scope of the project. The molecular structures involved in the development and progression of NSCLC will be determined and relations with the clinical, tumor-node-metastasis (TNM) staging and histology will be made. The development of a diagnostic kit for immediate clinical purposes and an electrochemical biosensor for quick on-site applications are targeted through the development of a number of antibody and aptamer formed against the most specific biomarker selected from the panel.

• Is there anything else we should know about you and your research?

Besides AKMARK, I am also in preparation of having a side project that aims for the development of a computational method to design inhibitors for prokaryotic two-component systems. In this project, I will be in collaboration with Prof. Maria Kontoyianni, SIUE: Southern Illinois University Edwardsville, School of Pharmacy.

• What was your greatest scientific disappointment in life till now?

So far I do not experience any memorable scientific disappointment in my life. :)

• What major research challenges and problems did you face yet? How did you handle them?

The major challenge which I faced so far in my scientific career was predicting the interaction between the prokaryotic two-component proteins. To be able to accurately predict the interactions between these proteins, I create a meta-predictor by using a support vector machine. By using this technique I integrated six different protein-protein interaction methods in a way to cover disadvantage of one method with the advantage of another one. The meta-predictor which I developed during this work is accessible via http://metapred2cs.ibers.aber.ac.uk/ and for more detailed information about the system the articles with the PMID IDs; PMID: 27378293 and PMID: 26384938 can be read.

• What's your all-time favourite bioinformatics package, and why?

For me, the best bioinformatics package is R/Bioconductor. The reason why I like this package is, it provides lots of useful tools for comprehensive analysis and comparison of high-throughput experimental data in an integrated manner and besides lots of the packages it provides, it is open source and also open for development. As a result, it provides strong and flexible ways to do science.

• In bioinformatics, do you see yourself in which of the following roles-scientist, analyst, developer, engineer or pure academician?

Scientist / Developer.

• What will you like to accomplish in next five years / ten years?

For my current research, I would like to design a pipeline to automatically integrate and analyse omics data for cancer research which will be specifically aiming for biomarker and novel drug target discovery. In addition to this, I also like to develop another pipeline for prokaryotic TCS protein structure prediction and inhibitor design.

• When you will be retired, what would you tell next generation bioinformaticians?

Bioinformatics is not all about scripting and researchers who study in this field should never expect a tool to do their analyses for them. Besides computational skills, a bioinformatician must have a strong biological background in his/her research area which will allow them to understand if anything went wrong during their run by only looking at the results instead of just blindly trusting the output of the bioinformatics tools.

• What you always miss in bioinformatics when you will no longer working in this field?

Bioinformatics is open to doing multi-discipliner research with scientists all around the world. As a result, while I studying in this field I can interactively learn a lot from wide range research community. I think this is the one thing which I will miss the most.

• If there will be bioinformatics company owned by you in future, What are your company focus and aim?

With the increasing amount of data in databases, there is already a massive need for effective methods to eliminate the manipulated data and reach to clean/useful information. As days pass, the requirement of data mining will be the first step of any research project. For this reason, the major goal of my bioinformatics company will be developing effective tools to eliminate manipulated datasets and information that exist in the literature and provide trustworthy clean information/datasets for researchers.

• How much bioinformatics change in 2050, according to your wild imagination?

Bioinformatics is a field that constantly and dynamically changes. As the bioinformatics progress, new tools and methods become available and they provide a better application of existing methods or totally new methods that offer an alternative solution to various biological problems. A long with these updates, developers also provide easy to use GUIs for most of the tools. Considering this, if the field carries on developing like this, every single researcher with a strong biological background can be able to perform bioinformatics analyses by him/herself without needing a professional help. As a result, almost all of the bioinformaticians will be responsible just for development of new methods/tools.

• What would one piece of advice you give someone who's trying to reinvent themselves and enter into bioinformatics sector?

Bioinformatics is a wide field with a lot of career options. Thus, if a researcher likes to step into this field first he/she should be clear about the branch of the bioinformatics they like to study in. Following to this decision they should first learn at least one programing language and investigate the ways of how other researcher employed that language in their researches and WHY? A researcher, in this field, should never create and use copy paste scripts but always must understand WHY the other researcher worked in that way. Knowing the answer of this question is the only way to learn bioinformatics. Besides, a researcher in the field of bioinformatics (from any branch) must always be good about the environmental control. In other words, one should always easily control input output directories, modify files or directories, annotate and modify employed scripts during the research and should not allow any confusion during the different stages of the research. Finally, they should not blindly trust the output of a tool/software but do a benchmarking test for each of the tools which they decided to utilise in their research. In addition to this, even if the tools pass the benchmarking, researchers should have a good biological background in their field to tell if anything when wrong during the process by only looking the output(s) of the employed pipelines/packages/tools.  

http://bioinfo.konkuk.ac.kr/synteny_portal/

Address of the bookmark: http://bioinfo.konkuk.ac.kr/synteny_portal/

We are now seeking a postdoc scholarship holder with strong background in transcriptomics to use this large collection of data for integrative studies. Focus will be on advanced bioinformatics and statistical analysis of data from high-throughput sequencing including integration with the other platforms.

The scholarship holder must have a PhD with an outstanding research and publication record and will be selected based on her/his excellence and her/his skills. A PhD should have been awarded less than five years before the deadline of the application. The scholarship holder must have a strong background in bioinformatics, computer science, computational biology or equivalent with a profound knowledge about biology and biostatistics.

Your complete application must be received at KTH no later than 2018-01-15.

https://www.kth.se/en/om/work-at-kth/stipendier/postdoctoral-scholarship-in-bioinformatics-with-focus-on-transcriptomics-and-data-integration-1.779571

• 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

1. the ontology itself, which is a set of terms with their precise definitions and defined relationships between them, and
2. the associations between gene products and GO terms, which are used to capture the existing knowledge about what each gene is known to do.

But the term gene ontology, or GO, is commonly used to refer to both, which is sometimes a source of potential confusion. In order to avoid this, here we will use the term “GO ontology” to describe the set of terms and their hierarchical structure and “GO annotations” to describe the set of associations between genes and GO terms.

There are 3 types of terms, or domains if you wish, in the gene ontology:

• Biological Processes (BP)
• Molecular Functions (MF)
• Cellular Components (CC)

Address of the bookmark: https://advaitabio.com/faq-items/understanding-gene-ontology/