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Bioinformatics 2020

Genomics and DNA analysis

06 November 2020

Things to do

This course teach how to interpret and understand the results of bioinformatic analyses. Most molecular biologists will work in team with (or hire) bioinformatic teams, so even if they do not use the tools, all molecular biologists need to understand what is the meaning of the results. It is important to speak the same language, and be aware of the key aspects that can lead to the experiment’s success or failure.


Here you will find the slides from the classes and other supplementary material. Notice that some things are said but not written, so you better take good notes. We recommend taking notes with pen and paper using the Cornell Method.


These are some of the papers we want to read and understand during this semester. The most important ones are marked in bold face. Start by reading those ones.


Protein Alignment



  • Staden, R. “A Strategy of DNA Sequencing Employing Computer Programs.” Nucleic Acids Research 6, no. 7 (1979): 2601–10.

  • Lander, E S, and M S Waterman. “Genomic Mapping by Fingerprinting Random Clones: A Mathematical Analysis.” Genomics 2, no. 3 (April 1, 1988): 231–39.

  • Pevzner, P A, H Tang, and M S Waterman. “An Eulerian Path Approach to DNA Fragment Assembly.” Proceedings of the National Academy of Sciences of the United States of America 98, no. 17 (August 14, 2001): 9748–53.

  • Chaisson, M, D Brinza, and P Pevzner. “De Novo Fragment Assembly with Short Mate-Paired Reads: Does the Read Length Matter?” Genome Research, December 3, 2008, 25.

  • Sims, David, Ian Sudbery, Nicholas E. Ilott, Andreas Heger, and Chris P. Ponting. “Sequencing Depth and Coverage: Key Considerations in Genomic Analyses.” Nature Reviews Genetics 15, no. 2 (2014): 121–32.

  • Bankevich, Anton, Sergey Nurk, Dmitry Antipov, Alexey a. Gurevich, Mikhail Dvorkin, Alexander S. Kulikov, Valery M. Lesin, et al. “SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing.” Journal of Computational Biology 19, no. 5 (2012): 455–77.

  • Li, Zhenyu, Yanxiang Chen, Desheng Mu, Jianying Yuan, Yujian Shi, Hao Zhang, Jun Gan, et al. “Comparison of the Two Major Classes of Assembly Algorithms: Overlap-Layout-Consensus and de-Bruijn-Graph.” Briefings in Functional Genomics 11, no. 1 (2012): 25–37.

  • Nagarajan, Niranjan, and Mihai Pop. “Sequence Assembly Demystified.” Nature Reviews. Genetics 14, no. 3 (2013): 157–67.

  • Wick, Ryan R., Mark B. Schultz, Justin Zobel, and Kathryn E. Holt. “Bandage: Interactive Visualization of de Novo Genome Assemblies.” Bioinformatics 31, no. 20 (2015): 3350–52.

  • Phillippy, Adam M. “New Advances in Sequence Assembly.” Genome Research 27, no. 5 (May 1, 2017): xi–xiii.


  • Dina Fine Maron. “Dirty Money.” Scientific American, 2017.

  • Jeff Leach. “Going Feral: My One-Year Journey to Acquire the Healthiest Gut Microbiome in the World,” January 2014.

  • Tyson, Gene W, Jarrod Chapman, Philip Hugenholtz, Eric E Allen, Rachna J Ram, Paul M Richardson, Victor V Solovyev, Edward M Rubin, Daniel S Rokhsar, and Jillian F Banfield. “Community Structure and Metabolism through Reconstruction of Microbial Genomes from the Environment.” Nature 428, no. 6978 (2004): 37–43.

  • Qin, Junjie, Ruiqiang Li, Jeroen Raes, Manimozhiyan Arumugam, Kristoffer Solvsten Burgdorf, Chaysavanh Manichanh, Trine Nielsen, et al. “A Human Gut Microbial Gene Catalogue Established by Metagenomic Sequencing.” Nature 464, no. 7285 (March 4, 2010): 59–65.

  • Ünal, Burcu. “Phylogenetic Analysis of Bacterial Communities in Kefir by Metagenomics.” Izmir Institute of Technology, Turkey, 2008.

  • Ünal, Burcu, and Alper Arslanoğlu. “Phylogenetic Identification of Bacteria within Kefir by Both Culture-Dependent and Culture-Independent Methods.” African Journal of Microbiology Research 7, no. 36 (2013): 4533–38.

  • Handelsman, Jo. “Metagenomics: Application of Genomics to Uncultured Microorganisms.” Microbiology and Molecular Biology Reviews 68, no. 4 (2004): 669–85.

  • Baker, Brett J., and Jillian F. Banfield. “Microbial Communities in Acid Mine Drainage.” FEMS Microbiology Ecology 44, no. 2 (2003): 139–52.

  • Wooley, John C., and Yuzhen Ye. “Metagenomics: Facts and Artifacts, and Computational Challenges.” Journal of Computer Science and Technology 25, no. 1 (2009): 71–81.

  • Sharpton, Thomas J. “An Introduction to the Analysis of Shotgun Metagenomic Data.” Frontiers in Plant Science 5 (June 16, 2014): 209.

  • Hunter, Chris I, Alex Mitchell, Philip Jones, Craig McAnulla, Sebastien Pesseat, Maxim Scheremetjew, and Sarah Hunter. “Metagenomic Analysis: The Challenge of the Data Bonanza.” Briefings in Bioinformatics 13, no. 6 (November 1, 2012): 743–46.

  • Teeling, Hanno, and Frank Oliver Glöckner. “Current Opportunities and Challenges in Microbial Metagenome Analysis–a Bioinformatic Perspective.” Briefings in Bioinformatics 13, no. 6 (December 1, 2012): 728–42.

  • Mande, Sharmila S, Monzoorul Haque Mohammed, and Tarini Shankar Ghosh. “Classification of Metagenomic Sequences: Methods and Challenges.” Briefings in Bioinformatics 13, no. 6 (November 1, 2012): 669–81.


  • Yates, Andrew, Kathryn Beal, Stephen Keenan, William McLaren, Miguel Pignatelli, Graham R.S. Ritchie, Magali Ruffier, Kieron Taylor, Alessandro Vullo, and Paul Flicek. “The Ensembl REST API: Ensembl Data for Any Language.” Bioinformatics 31, no. 1 (2015): 143–45.

  • Zerbino, Daniel R., Premanand Achuthan, Wasiu Akanni, M. Ridwan Amode, Daniel Barrell, Jyothish Bhai, Konstantinos Billis, et al. “Ensembl 2018.” Nucleic Acids Research 46, no. D1 (2018): D754–61.

Web references

NCBI Videos

These videos are complementary to our classes. They cover the same topics with more detail. Please watch them to understand better this course.







We have a lot of content to learn, and only 3 hours of contact every week. Fortunately, this semester we will teach online, following the flipped-classroom methodology. Each week the learning process will have five parts:


This course does not require knowledge of coding or programming, but it will always be a strong advantage —in this course and in professional life— to know how to code a program. You will need:


We follow partially the plan proposed by Sayres (2018)1. At the end of the course students should be able to: