國立虎尾科技大學 |

Computational thinking for life scientists /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computational thinking for life scientists // Benny Chor, Tel-Aviv University, Amir Rubinstein, Tel-Aviv University.
Author:	Chor, Benny,
other author:	Rubinstein, Amir,
Description:	1 online resource (209 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 25 Aug 2022).
Subject:	Biology - Data processing. -
Online resource:	https://doi.org/10.1017/9781108178327
ISBN:	9781108178327 (ebook)

Computational thinking for life scientists /
Chor, Benny,

Computational thinking for life scientists /Benny Chor, Tel-Aviv University, Amir Rubinstein, Tel-Aviv University. - 1 online resource (209 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 25 Aug 2022).

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.

ISBN: 9781108178327 (ebook)Subjects--Topical Terms:

563885
Biology
--Data processing.

LC Class. No.: QH324.2 / .C437 2022

Dewey Class. No.: 570.285

Computational thinking for life scientists /
LDR:02168nam a2200289 i 4500 001 1127429
003 UkCbUP
005 20220908111358.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 240926s2022||||enk o ||1 0|eng|d
020 $a 9781108178327 (ebook)
020 $z 9781107197244 (hardback)
020 $z 9781316647592 (paperback)
035 $a CR9781108178327
040 $a UkCbUP $b eng $e rda $c UkCbUP
050 0 0 $a QH324.2 $b .C437 2022
082 0 0 $a 570.285 $2 23
100 1 $a Chor, Benny, $e author. $3 1446817
245 1 0 $a Computational thinking for life scientists / $c Benny Chor, Tel-Aviv University, Amir Rubinstein, Tel-Aviv University.
264 1 $a Cambridge, United Kingdom ; New York, NY : $b Cambridge University Press, $c 2022.
300 $a 1 online resource (209 pages) : $b digital, PDF file(s).
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Title from publisher's bibliographic system (viewed on 25 Aug 2022).
520 $a Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.
650 0 $a Biology $x Data processing. $3 563885
650 0 $a Computational biology. $3 566357
650 0 $a Computer logic. $3 786340
700 1 $a Rubinstein, Amir, $d 1977- $e author. $3 1446818
776 0 8 $i Print version: $z 9781107197244
856 4 0 $u https://doi.org/10.1017/9781108178327