Teachers: 楊立威、張筱涵、羅中泉老師 (Profs LW Yang, HH Chang, CC Lo)

1. Michael C. Whitlock and Dolph Schluter. 2014. The Analysis of Biological
Data (Second Edition). Roberts and Company Publishers, Greenwood Village,
Colorado. (ISBN-10: 1936221489) https://www.amazon.com/Analysis-Biological-Data-
Michael-Whitlock/dp/0981519407 (@NTHU library)
2. Biological Sequence Analysis Probabilistic Models of Proteins and Nucleic
Acids (@NTHU library)
3. Peter Dayan & L. F. Abbott. Theoretical Neuroscience: Computational and
Mathematical Modeling of Neural Systems. The MIT Press (Physical and electronic
copies available @ NTHU library)

Date Topic Instructor
9/13 From the things you already knew (to some extent) – mean, SD,
variance, how is statistics related to probability? Hypothesis testing. Why does
statistics/probability constitute the basics of machine learning (examples on drug
development etc)? LW Yang
9/20 Read the math formula – index, difference between probability
(discrete function) and probability density (continuous function), Comparing two
means (doing it with your MS Excel sheet), learning from playing dynamics
programming games to align two biological sequences LW Yang
9/27 Distributions Rules Probability addition/multiplication, dependency,
conditional probability, marginal probability and Bayes' theorem LW Yang
10/4 Python quiz (5%), math quiz (5%) TA/LWYang
10/11 Build your first probabilistic model - a classifier, (Relative) Entropy,
Information Content, “Distance” between Distributions, Boltzmann Relation LW
10/18 Normalization – frequency vs proportion, normalization by controls, by
ranking, by probability LW Yang
10/25 Data types, sampling biases and rules, inference from samples I HH Chang
11/1 Inference from samples II HH Chang
11/8 Analyzing categorical data: goodness-of-fit test, contingency analysis HH
11/15 Correlation and Regression I HH Chang
11/22 Correlation and Regression II HH Chang
11/29 Models of neurons and synapses CC Lo
12/06 Models of synaptic plasticity and memory CC Lo
12/13 Matrix and linear algebra CC Lo
12/20 Stability and dynamical system theory CC Lo
12/27 Learning and decision making in biological neural networks CC Lo

Yang: two computational homework (15% each – Protein Sequence Aligner & CpG island
predictor using log-odd values), one math exam and one python exam (10%)
Chang: homework (30%)
Lo: homework (30%)

With programming workshop:
Python programming taught in 10 weeks + one session of basic Linux