It's been quite a while since I updated this tutorial series- better late than never? Introduction First, we determine the distribution our data comes from, or the likelihood, and any prior information is described using the prior distribution. Then we use Markov chain Monte Carlo to explore this posterior. Then we determine if we need… Continue reading Bayesian statistics part 4 – R tutorial

# Author: iambecomecomputational

## Application Statistics: PhD Student to Postdoc

In 2017 I was halfway through my PhD and frustrated with the opportunities available to me at my home institution. Conferences were rarely held even far away, and no travel funding. I thought even if I did apply, I would probably get rejected anyway. Apparently that mentality is common in women. So I started applying… Continue reading Application Statistics: PhD Student to Postdoc

## Preparing for grad school

You'll always worry about being smart enough, clever enough, reading and writing enough. You can always do remedial classes (I did and wow is it easier than when I was a freshman). Here's some things that might help you prepare for the hard parts of grad school. Therapist Absolutely necessary. Have you seen the data… Continue reading Preparing for grad school

## Workshop on Computational Plant Biology at PB2020 & Opportunities for Participants

Last year I held a workshop on collaboration in computational plant biology at pb2019. We went through a few examples of how computational biology is used in a variety of situations, discussed challenges in collaboration and communication. Participants were matched with potential collaborators at the end of the workshop. I received a lot of feedback… Continue reading Workshop on Computational Plant Biology at PB2020 & Opportunities for Participants

## Sartre’s PhD student

Let us consider this waiter in the cafe. His movement is quick and forward, a little too precise, a little too rapid. He comes toward the patrons with a step a little too quick. He bends forward a little too eagerly; his voice, his eyes express an interest a little too solicitous for the order… Continue reading Sartre’s PhD student

## How to teach yourself coding

I'm primarily a self-taught programmer. I have taken a handful of classes, which is precisely why I'm pro teach yourself. Having a vision for what you want to create with code makes everything so much easier. Pseudo code So, you have some idea about what you want to program. Start by writing pseudo-code. This is… Continue reading How to teach yourself coding

## Happy New Year!

Last year was very eventful for me. I've been a bit busy to write many blog posts but I'm ready to get back into it. Over the next year I'll be writing about my experiences in grad school, postdoc, and the transition; as well as some of the projects I've been working on and coding… Continue reading Happy New Year!

## Introduction to modeling: parameter estimation in R

This code introduces how to perform parameter estimation for a system of differential equations in R. First, the necessary packages and data are imported using code previously introduced in a previous post. R code available here. Due to computational constraints, the mathematical model we are using to fit to the data includes product inhibition. If product inhibition doesn't… Continue reading Introduction to modeling: parameter estimation in R

## Introduction to modeling and coding in R

After introducing students to a simple mathematical model describing enzyme kinetics, I introduced them to coding and modeling in R. Coding is traditionally done by first describing some coding 'rules', including ending the line with semicolons or how to define a variable. Personally I found these methods ineffective and frustrating. I took a few classes… Continue reading Introduction to modeling and coding in R

## Modeling demo: photosynthesis

This demo is intended to help students understand the connection between photosynthetic pigment function, light energy, and plant growth. The relative absorption of 8 wavelength ranges can be modified to represent an absorption spectra. These absorption spectra could be simplified to include one or two specific colors, or approximate an absorption spectra obtained in lab.… Continue reading Modeling demo: photosynthesis