References and other readings

Author
Affiliation

Jelmer Poelstra

CFAES Bioinformatics Core, Ohio State University

Published

August 25, 2025


The following references are assigned as reading, cited, and/or provided as further resources in the course.

Back to top

References

Abdill, Richard J., Emma Talarico, and Laura Grieneisen. 2024. “A How-to Guide for Code Sharing in Biology.” PLOS Biology 22 (9): e3002815. https://doi.org/10.1371/journal.pbio.3002815.
Allesina, Stefano. 2019. Computing Skills for Biologists: A Toolbox. Princeton, NJ: Princeton University Press,. https://doi.org/10.1515/9780691183961.
Andrews, S. 2010. FASTQC. A Quality Control Tool for High Throughput Sequence Data.
Aragona, Maria, Anita Haegi, Maria Teresa Valente, Luca Riccioni, Laura Orzali, Salvatore Vitale, Laura Luongo, and Alessandro Infantino. 2022. “New-Generation Sequencing Technology in Diagnosis of Fungal Plant Pathogens: A Dream Comes True?” Journal of Fungi 8 (7): 737. https://doi.org/10.3390/jof8070737.
Buffalo, Vince. 2015. Bioinformatics Data Skills [Reproducible and Robust Research With Open Source Tools]. First edition. Beijing: O’Reilly.
Di Tommaso, Paolo, Maria Chatzou, Evan W. Floden, Pablo Prieto Barja, Emilio Palumbo, and Cedric Notredame. 2017. “Nextflow enables reproducible computational workflows.” Nature Biotechnology 35 (4): 316–19. https://doi.org/10.1038/nbt.3820.
Dijk, Erwin L. van, Delphine Naquin, Kévin Gorrichon, Yan Jaszczyszyn, Rania Ouazahrou, Claude Thermes, and Céline Hernandez. 2023. “Genomics in the Long-Read Sequencing Era.” Trends in Genetics 39 (9): 649–71. https://doi.org/10.1016/j.tig.2023.04.006.
Ewels, Philip A., Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso, and Sven Nahnsen. 2020. “The Nf-Core Framework for Community-Curated Bioinformatics Pipelines.” Nature Biotechnology 38 (3): 276–78. https://doi.org/10.1038/s41587-020-0439-x.
Ewels, Philip, Måns Magnusson, Sverker Lundin, and Max Käller. 2016. “MultiQC: Summarize Analysis Results for Multiple Tools and Samples in a Single Report.” Bioinformatics 32 (19): 3047–48. https://doi.org/10.1093/bioinformatics/btw354.
Garrigós, Marta, Guillem Ylla, Josué Martínez-de la Puente, Jordi Figuerola, and María José Ruiz-López. 2025. “Two Avian Plasmodium Species Trigger Different Transcriptional Responses on Their Vector Culex pipiens.” Molecular Ecology 34 (15): e17240. https://doi.org/10.1111/mec.17240.
Grünwald, Niklaus J., Clive H. Bock, Jeff H. Chang, Alessandra Alves De Souza, Emerson M. Del Ponte, Lindsey J. du Toit, Anne E. Dorrance, et al. 2024. “Open Access and Reproducibility in Plant Pathology Research: Guidelines and Best Practices.” Phytopathology® 114 (5): 910–16. https://doi.org/10.1094/PHYTO-12-23-0483-IA.
Heyden, Sophie von der, Luciano B. Beheregaray, Sarah Fitzpatrick, Catherine E. Grueber, Yibo Hu, and Alison G. Nazareno. 2025. “Advancing Species Conservation and Management Through Omics Tools.” Molecular Ecology Resources 25 (5): e14123. https://doi.org/10.1111/1755-0998.14123.
Konkel, Zachary, and Jason C. Slot. 2023. “Mycotools: An Automated and Scalable Platform for Comparative Genomics.” BioRxiv. https://doi.org/10.1101/2023.09.08.556886.
Krueger, Felix. 2021. Trimgalore. https://github.com/FelixKrueger/TrimGalore.
Lee, Jun-Yeong. 2023. “The Principles and Applications of High-Throughput Sequencing Technologies.” Development & Reproduction 27 (1): 9–24. https://doi.org/10.12717/DR.2023.27.1.9.
Mahmood, Umer, Xiaodong Li, Yonghai Fan, Wei Chang, Yue Niu, Jiana Li, Cunmin Qu, and Kun Lu. 2022. “Multi-Omics Revolution to Promote Plant Breeding Efficiency.” Frontiers in Plant Science 13 (December). https://doi.org/10.3389/fpls.2022.1062952.
Manzoni, Claudia, Demis A Kia, Jana Vandrovcova, John Hardy, Nicholas W Wood, Patrick A Lewis, and Raffaele Ferrari. 2018. “Genome, Transcriptome and Proteome: The Rise of Omics Data and Their Integration in Biomedical Sciences.” Briefings in Bioinformatics 19 (2): 286–302. https://doi.org/10.1093/bib/bbw114.
Markowetz, Florian. 2015. “Five Selfish Reasons to Work Reproducibly.” Genome Biology 16 (1): 1–4. https://doi.org/10.1186/s13059-015-0850-7.
Nizamani, Mir Muhammad, Qian Zhang, Ghulam Muhae-Ud-Din, and Yong Wang. 2023. “High-Throughput Sequencing in Plant Disease Management: A Comprehensive Review of Benefits, Challenges, and Future Perspectives.” Phytopathology Research 5 (1): 44. https://doi.org/10.1186/s42483-023-00199-5.
Noble, William Stafford. 2009. “A Quick Guide to Organizing Computational Biology Projects.” PLOS Computational Biology 5 (7): e1000424. https://doi.org/10.1371/journal.pcbi.1000424.
O’Neil, Shawn T. 2019. A Primer for Computational Biology. Oregon State University. https://open.oregonstate.education/computationalbiology/.
Pereira, Rute, Jorge Oliveira, and Mário Sousa. 2020. “Bioinformatics and computational tools for next-generation sequencing analysis in clinical genetics.” Journal of Clinical Medicine 9 (1). https://doi.org/10.3390/jcm9010132.
Perkel, Jeffrey M. 2019. “Workflow Systems Turn Raw Data into Scientific Knowledge.” Nature 573 (7772): 149–50. https://doi.org/10.1038/d41586-019-02619-z.
Pinto, Yishay, and Ami S. Bhatt. 2024. “Sequencing-Based Analysis of Microbiomes.” Nature Reviews Genetics 25 (12): 829–45. https://doi.org/10.1038/s41576-024-00746-6.
Poinsignon, Thibault, Pierre Poulain, Mélina Gallopin, and Gaëlle Lelandais. 2023. “Working with Omics Data: An Interdisciplinary Challenge at the Crossroads of Biology and Computer Science.” In, 313–30. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3195-9_10.
Rai, Amit, Mami Yamazaki, and Kazuki Saito. 2019. “A New Era in Plant Functional Genomics.” Current Opinion in Systems Biology, Gene regulation, 15 (June): 58–67. https://doi.org/10.1016/j.coisb.2019.03.005.
Wang, Nian, George W. Sundin, Leonardo De La Fuente, Jaime Cubero, Satyanarayana Tatineni, Marin T. Brewer, Quan Zeng, et al. 2024. “Key Challenges in Plant Pathology in the Next Decade.” Phytopathology® 114 (5): 837–42. https://doi.org/10.1094/PHYTO-04-24-0137-KC.
Wilson, Greg, Jennifer Bryan, Karen Cranston, Justin Kitzes, Lex Nederbragt, and Tracy K. Teal. 2017. “Good Enough Practices in Scientific Computing.” PLOS Computational Biology 13 (6): e1005510. https://doi.org/10.1371/journal.pcbi.1005510.