The last post I made date back to 2 December 2021. What the hell, I would like to be more constant to dedicate more time to blogging but the work absorbs me. Despite this I do not give up. Writing and bringing content and what I learn on my journey into the world of bioinformatics it's a pleasure for me and I see it arouses interest so … slowly … really slowly …. did I already say slowly ??? … I will continue to bring content and not to abandon my dissemination activity.

Today is 25 Jenuary 2022 (Wow it is the first post of 2022. Urrà!!!). I'm in Turin and it's very cold. I took a break from work. In this period I have been involved in the study and construction of a pipeline for ATAC-seq analysis. But as always I try to dedicate some time to personal study and to increase my data science skills.

One of the things that is taking me a lot of study time is math and statistics. I have to be honest with you. I hate … I repeat I hate … math. When I am faced with complex formulas and arithmetic calculations, even simple ones, my brain starts to freeze, anxiety devours me together with the dear frustration that makes me depressed and insecure.

My problem with math starts from afar, I have never had teachers able to explain it correctly. It was presented to me as a subject to be memorized and it soon became abstract and difficult. When I decided to become a bioinformatician, I immediately asked myself:

*"Can I become a bioinformatician even if I suck at math?"*

Well I still don't know the answer even though I've seen a lot about it on the net. What I know well, however, is that I want to make peace with mathematics, I don't want to remain in this ignorance and fear. To do this I have perhaps taken the long way but I think it is the right one for me and to do this.

I have defined some milestones to make peace with math:

**Don't be afraid of your limits, challenge yourself and overcome them.****I'm not a mathematician and I don't have to become a mathematician, so I don't have to know all the mathematics but I have to orient myself in the mathematics that a bioinformatician needs.****I have to start from scratch, as if I were a child who approaches numbers and math for the first time (I know it's extreme but I think it's the best way to overcome the fear of math, at least for me).****I have to really understand what math is and I have to be patient.**

On the basis of the principles mentioned above, I began to study progressively. Starting from scratch to get to mathematics that is really useful for a bioinformatician. Below I have therefore reported some sources in order of complexity that I followed to learn, or better, to understand math.

**PRE-ALGEBRA:**Prealgebra (English Edition) ; Matematica di base: Aritmetica e pre-algebra (In Italiano). Alternative(Video).**ALGEBRA:**Algebra: A Complete Introduction ; Capire l'algebra: precorso di matematica in 29 giorni (Italiano); Alternative(Video: 1, 2 and 3).**STUDY OF A FUNCTION:**Studio di Funzioni (Italiano); English.**LINEAR ALGEBRA:**Linear algebra: foundations to frontiers or Mathematics for machine learning: linear algebra or Linear Algebra Khan.**CALCULUS:**Mathematics for machine learning: multivariable calculus; Calcolo in parole semplici (Italiano)**DISCRETE MATH:**Introduction to discrete mathematics for computer science specialization or Introduction to mathematical thinking.**USEFUL BOOKS:**How Not to Be Wrong: The Power of Mathematical Thinking; I numeri non sbagliano mai. Il potere del pensiero matematico; Contro l'ora di matematica: Un manifesto per la liberazione di professori e studenti; A Mathematician's Lament: How School Cheats Us Out of Our Most Fascinating and Imaginative Art Form (English Edition); Il museo dei numeri: Un avventuroso viaggio nel mondo della matematica per smettere di temerla e imparare ad amarla (Only in Italian). Avrei voluto capire la matematica (Only in Italian).

Well, I think I've given you some useful material and also given you some good ideas on how to study the math that a bioinformatician needs. Let me be clear. This study path is neither simple nor fast. It takes patience and dedication. But in the end, with difficulty, you will get a new dear friend … math. I haven't quite finished my studies yet but I can tell you right now that you can't love what you don't understand. Having undertaken this path of study in math is helping me to understand what mathematics really is and how a data scientist (as a bioinformatician is) can use it to his rescue. Furthermore, mathematics is fundamental for statistics which, paradoxically, is a subject that I love madly. But we will talk about this in week 6.

Now I make myself a nice cup of hot tea, put on some jazz music and get back to writing codes.

Ciao and see you soon.