Halfon Lab

Resources for Students and Postdocs

This page has links to articles and papers of general interest to graduate students and postdocs, especially those at the start of their careers.

"A Grad School Survival Guide": Andrew Gaudet, Science (2015) 347:1386.

"How to choose a good scientific problem": Uri Alon, Mol. Cell (2009) 35:726.

"How to give a good talk": Uri Alon, Mol. Cell (2009) 36:165. (And Uri Alon gives very good talks)

"Billboard Science": Kenall Power, Nature (2012) 483:113. Some tips on making effective research posters.

"The care and maintenance of your adviser": Kearns and Gardiner, Nature (2011) 469:570. Getting the most out of your PI.

"From trainee to tenure-track: ten tips": Tuuli Lappalainen, Genome Biology (2015) 16:132.

Think. Check. Submit: Choose the right journal for your research

Blog entry: Giving a Chalk Talk by Joan E. Strassmann

Writing a scientific article: A step-by-step guide for beginners: Ecarnot et al., European Geriatic Medicine (2015) 6:573.

"Ten Rules" series: PLoS Computational Biology publishes occasional brief articles in its "Ten Rules" series on topics such as preparing presentations, choosing a laboratory, forming collaborations, etc.

• Bourne. Ten simple rules for making good oral presentations. PLoS Comput Biol (2007) vol. 3 (4) pp. e77
• Bourne and Friedberg. Ten simple rules for selecting a postdoctoral position. PLoS Comput Biol (2006) vol. 2 (11) pp. e121
• Bourne and Korngreen. Ten simple rules for reviewers. PLoS Comput Biol (2006) vol. 2 (9) pp. e110
• Bourne and Chalupa. Ten simple rules for getting grants. PLoS Comput Biol (2006) vol. 2 (2) pp. e12
• Corpas et al. Ten simple rules for organizing a scientific meeting. PLoS Comput Biol (2008) vol. 4 (6) pp. e1000080
• Gu and Bourne. Ten simple rules for graduate students. PLoS Comput Biol (2007) vol. 3 (11) pp. e229
• Searls. Ten Simple Rules for Choosing between Industry and Academia. PLoS Comput Biol (2009) vol. 5 (6) pp. e1000388
  
• Vicens and Bourne. Ten simple rules to combine teaching and research. PLoS Comput Biol (2009) vol. 5 (4) pp. e1000358
• Vicens and Bourne. Ten simple rules for a successful collaboration. PLoS Comput Biol (2007) vol. 3 (3) pp. e44
• Logan et al. Ten simple rules for editing Wikipedia. PLoS Comput Biol (2010) vol. 6 (9) pp. e1000941
• Erren et al. Ten simple rules for doing your best research, according to Hamming. PLoS Comput Biol (2007) vol. 3 (10) pp. 1839-40
• Erren and Bourne. Ten simple rules for a good poster presentation. PLoS Comput Biol (2007) vol. 3 (5) pp. e102
• Pautasso, M. (2013). Ten Simple Rules for Writing a Literature Review. PLoS Computational Biology, 9(7), e1003149
• Mensh and Kording. Ten simple rules for structuring papers. PLoS Computational Biology (2017), 13(9), e1005619
• Zhang. Ten simple rules for doing a postdoc in pharma. PLoS Computational Biology (2021), 17(6), e1008989
• Leininger et al. Ten simple rules for attending your first conference. PLoS Computational Biology (2021), 17(7),e1009133
• Jabre et al. Ten simple rules for choosing a PhD supervisor. PLoS Computational Biology (2021), 17(9),e100930
• Zitomer et al. Ten simple rules for getting started with statistics in graduate school. PLoS Computational Biology (2022), 18(4), e1010033
• Hertz and McNeill. Eleven quick tips for properly handling tabular data. PLoS Computational Biology (2024), 20(11), e1012604

Statistical analysis

• Ten simple rules for getting started with statistics in graduate school. PLoS Computational Biology (2022), 18(4), e1010033
• Tidy Data. Journal of Statistical Software, 59(10), 1-23
• The ASA Statement on p-Values: Context, Process, and Purpose. The American Statistician (2016), 70(2), 129-133
• "Error Bars in Experimental Biology": Cumming, Fidler and Vaux, Journal of Cell Biol. (2007) 177:7. Eight simple rules to assist with effective use and interpretation of error bars.
• "Graphical assessment of tests and classifiers": Altman and Krzywinski, Nature Methods (2021) 18:839. Confusion matrices, ROC curves, and PR curves.

"Points of View": Nature Methods' column on effective visual presentation of scientific data.

• "Design of data figures": Bang Wong, Nat Meth (2010) 7:665. What types of graphs are most effectively interpreted?
• "Color coding": Bang Wong, Nat Meth (2010) 7:573. Notes on effective use of color in presentations and publications.
• "Salience": Bang Wong, Nat Meth (2010) 7:775. How to make your visual images stand out.
• "Gestalt Principles I": Bang Wong, Nat Meth (2010) 7:863. Grouping and composition.
• "Gestalt Principles II": Bang Wong, Nat Meth (2010) 7:941. Composition and layout.
• "Negative Space": Bang Wong, Nat Meth (2011) 8:5. Effective use of white space in poster layout.
• "Points of Review (part 1)": Bang Wong, Nat Meth (2011) 8:101. Design principles for figures in journals.
• "Points of Review (part 2)": Bang Wong, Nat Meth (2011) 8:189. More design principles for figures in journals.
• "Typography": Bang Wong, Nat Meth (2011) 8:227. Effective use of typefaces.
• "Color Blindness": Bang Wong, Nat Meth (2011) 8:441. Making sure everyone can see the color information in your figures and presentations.
• "Arrows": Bang Wong, Nat Meth (2011) 8:701. Tips on using and formatting arrows and leaders.
• "Layout": Bang Wong, Nat Meth (2011) 8: 783. Design principles for poster and slide layout.
• "Salience to relevance": Bang Wong, Nat Meth (2011) 8:889. Making sure the most noticible features are the most important.
• "The design process": Bang Wong, Nat Meth (2011) 8:987. The value of 'design' itself.
• "Labels and callouts": Martin Krzywinski, Nat Meth (2013) 10:275. Making good figure labels.
• "Elements of visual style": Martin Krzywinski, Nat Meth (2013) 10:371. Effective figure design principles.

For students beginning work on computational/dry lab projects:

• Baxter et al. Scientific software development is not an oxymoron. PLoS Comput Biol (2006) vol. 2 (9) pp. e87
• Dudley and Butte. A Quick Guide for Developing Effective Bioinformatics Programming Skills. PLoS Comput Biol (2009) vol. 5 (12) pp. e10000589
• Noble and Lewitter. A Quick Guide to Organizing Computational Biology Projects. PLoS Comput Biol (2009) vol. 5 (7) pp. e1000424
• Wilson. Where's the real bottleneck in scientific computing?. American Scientist (2006)
• Ekmekci et al. An introduction to Programming for Bioscientists: A Python-Based Primer. PLoS Comput Biol (2016) vol. 12(6) pp. e1004867
• Wilson. Good enough practices in scientific computing. PLoS Comput Biol (2017) vol. 13 (6) pp. e1005510
• Abdill et al. A how-to guide for code sharing in biology. PLoS Comput Biol (2024) vol. 22 (9) pp. e3002815

Bioinformatics "Primers" from the occasional Nature Biotechnology series:

• Eddy. What is dynamic programming?. Nat Biotechnol (2004) vol. 22 (7) pp. 909-10
• Eddy. Where did the BLOSUM62 alignment score matrix come from?. Nat Biotechnol (2004) vol. 22 (8) pp. 1035-6
• Eddy. What is Bayesian statistics?. Nat Biotechnol (2004) vol. 22 (9) pp. 1177-8
• Eddy. What is a hidden Markov model?. Nat Biotechnol (2004) vol. 22 (10) pp. 1315-6
• Eddy. How do RNA folding algorithms work?. Nat Biotechnol (2004) vol. 22 (11) pp. 1457-8
• D'haeseleer. How does gene expression clustering work?. Nat Biotechnol (2005) vol. 23 (12) pp. 1499-501
• D'haeseleer. What are DNA sequence motifs?. Nat Biotechnol (2006) vol. 24 (4) pp. 423-5
• D'haeseleer. How does DNA sequence motif discovery work?. Nat Biotechnol (2006) vol. 24 (8) pp. 959-61
• Brent. How does eukaryotic gene prediction work?. Nat Biotechnol (2007) vol. 25 (8) pp. 883-5
• Kingsford and Salzberg. What are decision trees?. Nat Biotechnol (2008) vol. 26 (9) pp. 1011-3
• Trapnell and Salzberg. How to map billions of short reads onto genomes. Nat Biotechnol (2009) vol. 27 (5) pp. 455-7
• Merico et al. How to visually interpret biological data using networks. Nat Biotechnol (2009) vol. 27 (10) pp. 921-4