Update README.md

Author: Gagniuc

README.md

@@ -1,9 +1,6 @@
 # Bioinformatics HTML5 Implementations
-Bioinformatics HTML5 Implementations
-
-
-These Bioinformatics HTML5/JS files accompany the book entitled: Algorithms in Bioinformatics: Theory and Implementation, and they are compatible with all internet browsers. These algorithms include more than 120 open-source implementations that describe the following: 1. A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast. 2. A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations. 3. Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices. 4. A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields. 5. An examination of information and entropy, including sequence logos and explanations related to their meaning. 6. An exploration of the current state of bioinformatics, including what is known and what issues are usually avoided in the field. 7. Native computer implementations in the context of the field of Bioinformatics. 8. Extensive worked examples with detailed case studies that point out the meaning of different results.
 
+These Bioinformatics HTML5/JS files accompany the book entitled: <i>Algorithms in Bioinformatics: Theory and Implementation</i>, and they are compatible with all internet browsers. These algorithms include more than 120 open-source implementations that describe the following: a) A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast. b) A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations. c) Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices. d) A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields. e) An examination of information and entropy, including sequence logos and explanations related to their meaning. f) An exploration of the current state of bioinformatics, including what is known and what issues are usually avoided in the field. g) Native computer implementations in the context of the field of Bioinformatics. h) Extensive worked examples with detailed case studies that point out the meaning of different results.
 
 ![screenshot](https://github.com/Gagniuc/Bioinformatics-HTML5-Implementations/blob/main/bio%20logo.png)
 ![screenshot](https://github.com/Gagniuc/Bioinformatics-HTML5-Implementations/blob/main/Eng1.png)