Reading material.
My professional journey in a sense has been a wild ride. As an interdisciplinary young researcher, I need to know enough bits of math, statistics, genetics, plant science, image processing, and machine learning. Jack of all trades, master of none.
Below is a list of material that I've read at some point to get a quick understanding of a specific discipline or sub-discipline. The list is by no means exhaustive. I do not claim that is the optimal path to learn, in any definition of the word optimal. It is just the list of material that I happened to stumble upon. I cannot stress enough the importance of insightful conversations with peers and faculty from different areas of expertise. Such insight is vital to connect the dots laid down by the reading material.
- Topological Data Analysis in General
- G. Carlsson, Topology and Data, Bulletin of the American Mathematical Society 46, no. 2 (2009): 255–308. DOI: 10.1090/S0273-0979-09-01249-X
- E. Amézquita, M. Quigley, T. Ophelders, E. Munch, D. Chitwood. The shape of things to come: Topological Data Analysis and biology, from molecules to organisms. Developmental Dynamics 2020; 1--18. DOI: 10.1002/dvdy.175
- E. Munch. A User's Guide to Topological Data Analysis. Journal of Learning Analytics, 2017. DOI: 10.18608/jla.2017.42.6
- Plenty of useful reading and software links here
- Image processing
- L Shapiro, G Stockman. Computer Vision. Prentice Hall, 2001.
- M Nixon, A Aguado. Feature Extraction & Image Processing for Computer Vision. Academic Press. 2012.
- The SciPy community. scipy.ndimage module
- Machine Learning
- T Hastie, R Tibshirani. J Friedman. The Elements of Statistical Learning. Data Mining, Inference, and Predition. Springer, 2017.
- R Vidal, Y Ma, S Sastry. Generalized Principal Component Analysis. Springer 2016.
- Y Yao. A Mathematical Introduction to Data Science. Draft. 2017
- Biology and genetics
- A Griffiths, S Wessler, S Carroll, J Doebley. Introduction to genetic analysis. W.H. Freeman Company. 2012.
- S Uygun, C Peng, M Lehti-Shiu, R Last, S Shiu. Utility and Limitations of Using Gene Expression Data to Identify Functional Associations. PLoS Comput Biol 12(12) DOI: 10.1371/journal.pcbi.1005244
Xray CT scan of scarlet emperor mandarins
Observing apple vasculature
Couple of corn ears
Interior of a corn ear
Agave crossed with Manfreda
A cavernous bell pepper!
Quoting Dan C: "Everytime you see a cactus, you should feel awe."
Spiraling with haworthia