Many years ago, I (Sebastian) started writing a textbook on the algorithmics (and, to a lesser extent, statistics and machine learning) behind computational mass spectrometry. Unfortunately, I never found the time to finish it. Consequently, I have decided I want to release it “into the wild” now, and hope that it ripens with the customer. Software companies have been following that strategy for decades, so what could possibly go wrong?
I will post updated versions of the lecture notes slash textbook, so please check regularly in case you find it useful.
I have put a somewhat lengthy disclaimer at the beginning of the textbook, explaining all the things it is not — and, also explaining what I am not. Please, keep that in mind when reading it.
If you find any errors in the manuscript, please send me an email and I am happy to correct them! (For the chapters and sections marked “work in progress”, these are obviously incomplete, so no need for an email there.) Also, if I am missing something that must be covered in the script, please let me know. If you want to contribute, even better!
Edit: Manor pointed out a number of errors on this page, including the false friend “script” — which means “lecture notes” in German, but not in English. I don’t know how to call it now, “textbook” or “lecture notes”? Whatever. Whenever you see “script” in the lecture notes, please do a global replace by “lecture notes” or “textbook”.
- version 0.6.0 of the textbook (Feb 27, 2019)
- version 0.7.0 of the textbook (Mar 20, 2019) — I have mostly “finished” the chapters on p-values and decoy databases; I hope that someone who knows more about statistics than I do, can tell me where I erred.