The very best book on Calculus and includes the material for all three semesters. You've probably seen this material before if you are CS or EE.

A good cheap text on probability and statistics and also a source of solved problems. Statistics is a vital skill in bioinformatics.

Per topic, there are a few pages of theory & equations, problems with solutions worked out extensively, & some problems with answers but no extensive solution. The format is the same as in a 2 semester college freshman physics sequence. The 1st part covers vectors, mechanics, fluids, & thermodynamics. The 2nd part covers electricity, magnetism, & optics. The last 7 chapters intro modern physics.

A self-study aid including alternate strategies for solving problems, supplemental explanations for the most difficult material, and self tests. Includes approximately 400 worked examples and 800 practice test questions with answers designed to help you master the material.

Perfect for summarizing the previous text and going into detail. It is an excellent review with some practice questions and charts in each section that match the textbook.

Beautifully written textbook presenting the canonical version of what is currently known about cellular biology at the molecular level. The illustrations are clear & the text is easy to follow. The only shortcoming of the book is that, necessarily, it stays above the messy details in order to maintain clarity. Prereqs are two semesters each of biology and chemistry.

Reading this book will not make you a molecular biologist, but it will allow you to talk reasonably intelligently to one. I recomend this book very highly to anyone who has an interest in this field, but doesn't know much about it. It is a great stepping stone to more complex texts and papers.

Bridges the gap between conceptual understanding & actual application while emphasizing problem-solving skills. All aspects of spectroscopy have been updated and enhanced, relevant photographs have been added, & many apps to polymer chemistry have been integrated throughout. Increased focus on & discussions of thiols & sulfides, stereochemistry, & mechanisms. Prereq is general chemistry.

All about what you need to succeed in o-chem. The examples every 3-5 pages are a great way to test yourself and break the monotony of reading. He provides short examples to illustrate his points but doesn't drone on any topic - you should utilize your text for more information. There is a part 2 to this book for the second semester of o-chem.

Lucid with detailed, "easy to understand" conversational explanations of various pertinent topics in biochemistry. Great emphasis had been placed on the fundamentals and how to implement these principles in solving biochemistry associated problems.

Prereq is 1st year physics and chemistry. Difficult mathematical concepts are integrated along with the appropriate topics & presented in a concise fashion. The first half of the text discusses topics in quantum chemistry while the rest deals with thermodynamics, statistical mechanics, & kinetics. All equations are backed by clear explanation & mathematical derivation.

Targets the novice. However, doesn't skimp on the critical, classic database issues such as the outer join, choosing primary and alternate keys, data normalization, good data modeling, & the differences between physical & logical design. Don't dismiss this if you think that you are already pretty knowledgeable. Databases are critical to bioinformatic techniques.

The second half of Tisdale's tutorial on Perl that features bioinformatic problem solving while teaching the language.

Focuses on practical techniques without unnecessary diversion into the detail of molecular biology or CS. It is a book about various tools and how to use them. Well worth reading before doing a bioinformatics course or degree.

Algorithm design is fundamental to bioinformatics, and even CS & EE majors can have trouble with this topic. This is a gentle intro to the subject versus the graduate text written by Cormen et al that people often struggle with.

Great for learning/reviewing math and how it can be applied to biological system modeling. The book is great for 3 reasons. First, it is impossible NOT to understand the material. 2nd, it really encourages the reader to go out & MODEL something with its dozens of inspiring & high-quality exercises & research projects. Finally, it provides insight into biology's qualitative aspects.