Class 1: Why? How?

Methodology of Scientific Research

Andrés Aravena, PhD

February 28, 2023

Welcome to

Methodology of Scientific Research

Methodology of Scientific Research

also known as MSR

also known as MıSıR

also known as 🌽

Today’s questions

Who
Why
How
What

Who?

I am Andres Aravena

  • Assistant Professor at the Molecular Biology and Genomics Department, Istanbul University
  • Mathematical Engineer, U. of Chile
  • PhD Informatics, U Rennes 1, France
  • PhD Mathematical Modeling, U. of Chile
  • not a Biologist
  • Applied Mathematician who can speak “biologist language”

What about you?

Why?

Why are you here?

Answer now with your voice

What?

Specific Goal

In this course we will speak about

Design of Experiments

We will learn to design better experiments and achieve higher scientific impact

How?

Generic goals

We wan to help you to become

  • Better molecular biologists
  • Better scientists
  • Better professionals
  • Better citizens

Better molecular biologists

  • Lower failure rate in your experiments

  • Do better experiments

  • Ask better questions

  • Achieve larger impact

Better scientists

  • Ask better questions

  • Propose better answers

  • Create Knowledge, not only Data

Better professionals

  • Perhaps you will change your career later in life

  • Whatever you do, do your best work

  • Always follow good practices

Better citizens

Perhaps you will win the lottery
(or inherit many million dollars from a distant uncle)

and you do not work anymore

Still, you need to understand the world

Enough so big companies cannot fool you

We need to see the Big Picture,
How did we get to here and now?

Why not just
“Good Scientists”?

(a parenthesis)

Earthquakes and Fatalities

Earthquakes Chile and Turkey

Fatalities and Magnitude

Since 1990. Richter scale, rounded to nearest integer

People know how to make safe buildings

Beyond Technical knowledge

Earthquakes do not kill people

Bad building protocols kill people

People know how to make safe buildings

They chose not to do so

We need good professionals and good citizens

Not only good Molecular Biologists

We need to learn and use Good Practices

We need to see the Big Picture

Tools & Good Practices

Lab Notebook

One of the essential good-practices of laboratory work is the Lab Notebook

They are essential if you want to get a patent for something you create

They are essential to carry long term experiments

We encourage you to use a good quality notebook every day

Do not trust your memory

Google Calendar

This is a communication device

  • Between you and your collaborators
  • Between tomorrow and today

Learn to use it

Share your calendar with me
(time usage, not necessarily all details)

Keep it updated and honest

Google Groups

This is the main way to discuss

I will make announcements there

You can discuss with your classmates there

Learning is a team sport. Nobody learns alone

Learn to work in teams. Team players get better jobs

Google Docs

This will be the main tool we will use

The weakest part of our education is writing

To make you a better scientist, we will ask you to write

I will use this tool to give you feedback

Google Drive

Everything that is not text should be shared through a cloud disk service

  • Dropbox
  • iCloud
  • OneDrive
  • Google Drive

Our life will be easy if we use Google Drive for this course.
It works well with Google Docs

Do you have a Google account?

Yes, you have one

Your student email account (@gor.iu.edu.tr) is a valid Google account

Course’s Homepage

Our homepage is at https://www.dry-lab.org/blog/2023/msr/

It is part of my blog https://www.dry-lab.org/

Homework and class slides are published there

I also have a YouTube channel https://www.youtube.com/@dr.andresaravena

Course plan

  • Asking good questions
  • Observing nature
    • Estimating
    • Measuring
    • Evaluating uncertainty
  • Finding reasonable theories
  • Testing theories with experiments

Key words

  • Estimation and Guesstimation
  • Order of magnitude
  • Confidence Intervals
  • Error propagation
  • Uncertainty budget
  • Dimensional Analysis
  • Linear models
  • Factorial design