Preface

The employment of computers, software tools, and internet services in basic sciences and medicine has led to changes in investigation methodologies. This occurrence resulted in the establishment of multidisciplinary sciences involving bioinformatics and systems biology. The computational multidisciplinary sciences represented new types of studies and laboratories. In silico investigations and dry laboratories have been the invaluable products of these sciences. The serious and continuous activities in this regard led to the accumulation of a huge amount of digital data (bioinformatic data) in the form of databases. These progressions and facilities resulted in invaluable outcomes such as computational biology and chemistry. I call them soft biology and chemistry.

The reason for the success and progression in soft biology and chemistry is the appearance of effective and precise bioinformatic software tools and databases such as the National Center for Biotechnology Information (NCBI) (https://www.ncbi.nlm. nih.gov/), Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.genome. jp/kegg/), and Research Collaboratory for Structural Bioinformatics PDB (RCSBPDB) (https://www.rcsb.org/).

Visualization and 3-dimentionization of different biomolecules, structures, and complexes are the most fantastic facilities that are provided and represented by bioinformatics, systems biology, computational biology, and chemistry.

The results of traditional investigations within wet labs by molecular biologists, biologists, biochemists, and chemists produced only raw data including nucleotides and amino acid sequences.

With the appearance of bioinformatics and the use of computational technologies, we are able to visualize these data to have their putative spatial configurations and conformations. Today, we are able to 3-dimensionalize the discovered raw data to have a limited imaging capability of their natural structure to understand the related characteristics, practicalities, and functionalities.

Moreover, the use of computational biology and chemistry has had effective consequences in pharmaceutics. As we know, the traditional procedure of preparation and provision of a drug or antibiotic includes several control and check processes in different levels of assays. These procedures and processes cost a lot of money and takes a long duration of time.

Recruitment of computational biology and chemistry represents a great opportunity for pharmaceutics. Drug designing is a brilliant bonus to pharmaceutics to shorten technical procedures and duration of time to reduce the costs of drugs and antibiotics.

All in all, we are at the beginning point of the soft biology and chemistry pathway. The progressions of these scientific disciplines support us to have incredible imaging, illustration, and interpretation of the obtained raw data in traditional wet labs. In the future we can have a precise image of the reason of spatial architecture of different biomolecules and their interactions with other structures and complexes. The dry labs determine the future of biology and chemistry!

**II**

**Chapter 6 97**

From Bioinformatics to Computational Biology **119**

**Chapter 7 121**

Hydrazone-Based Small-Molecule Chemosensors *by Thiago Moreira Pereira and Arthur Eugen Kümmerle*

Systems Glycobiology: Past, Present, and Future

**Section 5**

*by Songül Yaşar Yıldız*

The book "Computational Biology and Chemistry" is a collection of invaluable results and outcomes obtained by global and international scientists. This book involves seven chapters in five sections.

The first chapter is written by the editor and it completes the first section of the book. This chapter has a deep look at the background and historical features regarding the establishment of bioinformatics and computational biology and chemistry.

Section two comprises the single chapter (Chapter two) entitled: "Search Proteins Based on Human-Specific Availability Scores of Short Constituent Sequences: Identification of a WRWSH Protein in Human Testis". This chapter presents great information regarding in vitro-in silico studies.

Section three includes two chapters entitled: "Bioinformatics as a Tool for the Structural and Evolutionary Analysis of Proteins" and "Scaffolding Contigs Using Multiple Reference Genomes". These chapters offer brilliant information in association with the importance of bioinformatics and the related software tools and databases for analyzing proteins and genomes.

Section four contains two chapters, entitled: "Biological Evaluation and Molecular Docking Studies of a Double Active Pharmaceutical Ingredient, Benzalkonium Ibuprofenate" and "Hydrazones: An Important Scaffold to Construct Fluorescent Chemosensor for Biological purposes". These chapters provide fabulous information in the fields of computational biology and chemical monitoring.

Section five as the final section involves Chapter seven entitled: "Systems Glycobiology: Past, Present, Future". This chapter reveals the linkage between bioinformatics, databases, systems biology, and computational biology. An informative chapter with fantastic outcomes!

I, as the Editor of the book "Computational Biology and Chemistry", am honored and thankful to have marvelous cooperation and collaboration with valuable scientists from different countries and continents. They contributed as informative authors in this brilliant book. This book offers up-to-date information in the field to readers worldwide.

And finally, I have special thanks to my Italian colleague Dr. Nicola Bernabò from Università Degli Studi di Teramo, who collaborated with me as an invaluable Co-editor, Dolores Kuzelj the Author Service Manager, Lucija Tomicic-Dromgool and Martina Usljebrka Kauric the Commissioning Editors of IntechOpen for their excellent collaboration, management, and arrangement for preparing this valuable book.

### **Dr. Payam Behzadi**

Department of Microbiology, College of Basic Sciences, Islamic Azad University, Shahr-e-Qods Branch, Tehran, Iran

**Nicola Bernabò**

**1**

Section 1

Introduction

Faculty of Bioscience, University of Teramo, Teramo, Italy

Section 1 Introduction

**3**

chapter.

**Chapter 1**

biology."

*Payam Behzadi*

Soft+science).

bench within the wet labs [2].

desktop work [2] and laptop biology [1].

to Soft Biology

**1. Experimentation and computation**

ence" term depicted "mathematics and algorithms" [1].

represent new terms "hard biology" and "soft biology."

"hard science" and "soft science." The results were as follows:

Introductory Chapter: From Hard

On the evening of Monday, April 13, 2020, during "the Wuhan-China virus (COVID-19) Home-Self Quarantine Era," I was drinking coffee and simultaneously searching on Google Scholar to find some valuable papers regarding "computational

Among a mass of article links, an article entitled "laptop biology" [1] attracted me. I began to read this paper carefully and found some valuable terms including "hard science" and "soft science." Indeed, the term "soft science" was used for "experimentation, classification, observation and intuition," while the "hard sci-

Then I checked https://www.thefreedictionary.com/ and searched for the terms

• "Hard Science: one of the natural or physical sciences, such as physics, chemistry, biology, geology, or astronomy, any of the natural or physical sciences, in which hypotheses are rigorously tested through observation and experimentation" (https://www.thefreedictionary.com/hard+science).

• "Soft Science: a science, such as sociology or anthropology, that deals with humans as its principle subject matter, and is therefore not generally considered to be based on rigorous experimentation, any of the scientific disciplines, as those which study human behavior or institutions, in which strictly measurable criteria are difficult to obtain" (https://www.thefreedictionary.com/

Although the meanings of these terms were very different from what I thought, I liked them. Due to this fact I found that it is better to use my terminology talent to

I used the term "hard biology" for experimental (in vitro, in vivo, and in situ investigations) biology. This term has a direct deal with experimentation and work

In contrast to "hard biology," I used the term "soft biology" based on in silico or

I hope that these terms are useful for the readers of this book and other scientists around the world. With this background I begin the main text of the introductory

### **Chapter 1**

## Introductory Chapter: From Hard to Soft Biology

*Payam Behzadi*

### **1. Experimentation and computation**

On the evening of Monday, April 13, 2020, during "the Wuhan-China virus (COVID-19) Home-Self Quarantine Era," I was drinking coffee and simultaneously searching on Google Scholar to find some valuable papers regarding "computational biology."

Among a mass of article links, an article entitled "laptop biology" [1] attracted me. I began to read this paper carefully and found some valuable terms including "hard science" and "soft science." Indeed, the term "soft science" was used for "experimentation, classification, observation and intuition," while the "hard science" term depicted "mathematics and algorithms" [1].

Then I checked https://www.thefreedictionary.com/ and searched for the terms "hard science" and "soft science." The results were as follows:


Although the meanings of these terms were very different from what I thought, I liked them. Due to this fact I found that it is better to use my terminology talent to represent new terms "hard biology" and "soft biology."

I used the term "hard biology" for experimental (in vitro, in vivo, and in situ investigations) biology. This term has a direct deal with experimentation and work bench within the wet labs [2].

In contrast to "hard biology," I used the term "soft biology" based on in silico or desktop work [2] and laptop biology [1].

I hope that these terms are useful for the readers of this book and other scientists around the world. With this background I begin the main text of the introductory chapter.

### **2. Biology and computer**

Undoubtedly the famous physical chemist from the USA, Margaret Dayhoff (1925–1983), the mother and father of bioinformatics, was the key scientist who employed computers and the related software tools in biochemistry [3, 4].

Indeed, it was Dayhoff who understood the importance of computers and computational methods not only in biology but also in medicine [4].

In 1960, Dayhoff as the Associate Director of the National Biomedical Research Foundation began her collaboration with her physicist colleague, Robert S. Ledley, who, like Dayhoff, was interested in employing computers in biomedical sciences [3, 5, 6].

The outcome of their scientific collaboration (Dayhoff-Ledley) in the period of 1958–1962 led to a computer program COMPROTEIN (coded FORTRAN) which was designed for IBM 7090. The software COMPROTEIN (a de novo sequence assembler) was able to determine the primary structure of protein throughout the Edman peptide sequencing data [3, 7].

The amino acid one-letter coding system was founded by Dayhoff [3, 8]. Dayhoff and Eck continued their scientific activities by publishing the first edition of the invaluable book entitled *Atlas of Protein Sequence and Structure* in 1965 which involved 65 protein sequences [3, 4, 9]. The fourth edition of *Atlas of Protein Sequence and Structure* which was published in 1969 included more than 300 protein sequences. So, this atlas established the first database of biological sequence [3, 4]. Interestingly, the sequence alignment of biopolymers was started by proteins not DNA molecules. This claim is proven by representing a 12-sequenced DNA fragment in 1971 [4].

### **3. Molecular biology and computer**

During the golden decade between the years 1970 and 1980, the DNA language was decoded. However, the genetic codes of 64 codons were decoded in 1968 [3, 10]. Sanger's sequencing method of DNA based on "plus and minus" strands was performed 25 years after the recognition of the first protein sequence [3, 11, 12]. 1979 is the historical year for using the first software for Sanger's DNA sequencing method. In the paper published by Rodger Staden in 1979 via the journal of *Nucleic Acids Research*, the applied programs including OVRLAP, XMATCH, and FILINS (coded FORTAN) were described [3, 13].

During the years of 1980–1990, the application of computational sciences significantly increased. In 1983, the polymerase chain reaction (PCR) was invented by Kary B. Mullis (1944–2019 (https://www.nytimes.com/2019/08/15/science/karyb-mullis-dead.html)). Kary Banks Mullis as an American biochemist invented a valuable molecular method which was based on in vitro synthesis of DNA [14–16]. So, by the discovery of DNA molecules in the 1950s, and in consequence the early application of pro-computers, invention of molecular and sequencing methods, and utilizing Internet services within a short duration, it seems that several revolutionized features have happened in molecular biology [17].

Although computers and the related software tools were employed since the 1960s in biology, it was in the limited scales. I believe that by the invention of PCR as an in silico-in vitro (dry lab-wet lab) technology and its flying speed as a general molecular biology approach changed the traditional methodologies. By global generalization of PCR, the use of Internet services, computers, and software tools got significant acceleration. In this regard, designing different primers in large and global scales led to progression of in silico studies and appearance of dry labs within the wet labs.

**5**

**Author details**

**Conflict of interest**

Payam Behzadi

Islamic Azad University, Tehran, Iran

provided the original work is properly cited.

Department of Microbiology, College of Basic Sciences, Shahr-e-Qods Branch,

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

\*Address all correspondence to: behzadipayam@yahoo.com

*Introductory Chapter: From Hard to Soft Biology DOI: http://dx.doi.org/10.5772/intechopen.92572*

www.ddbj.nig.ac.jp/index-e.html) [18].

which all the consumers should be grateful for.

sive in silico studies, dry labs, and software tools.

The authors declare no conflicts of interest.

But the important question is:

USB flash drives with different bioinformatics software tools!

"How does biology get more softened in the future?"

and is continued to be more softened by computational biology!

Due to this fact, during a very short time, a mass of raw data was obtained by scientists around the world, and these data got stored within different biological databases like the National Center for Biotechnology Information (NCBI) (https:// www.ncbi.nlm.nih.gov/), European Molecular Biology Laboratory (EMBL) (https://www.embl.org/), Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.genome.jp/kegg/), and DNA Data Bank of Japan (DDBJ) (https://

At the same time, these giant databases began to give more free software tools, information, and other services. These features have led to establishing 1637 free online databases (http://www.oxfordjournals.org/nar/database/c/) up to now [19]. Today, some databases including The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (https://www.rcsb.org/) serve its global users for free. 3D macromolecular structure data is one of the most popular products which scientists and researchers use for free around the world [20]. Since 1971 when the US data center of RCSB PDB was founded, it provided digital data in biology for its users with open-access policy [20], an opportunity

All in all, soft biology was founded in the 1960s with a low speed, but it accelerated by the invention of PCR in the 1980s. The PCR invention softened the science of biology throughout Internet services, an occurrence which resulted in progres-

Today, a biologist is recognized by her/his laptop, Internet connection, and filled

Hence, hard biology got softened by establishing the science of bioinformatics

*Introductory Chapter: From Hard to Soft Biology DOI: http://dx.doi.org/10.5772/intechopen.92572*

*Computational Biology and Chemistry*

Edman peptide sequencing data [3, 7].

**3. Molecular biology and computer**

(coded FORTAN) were described [3, 13].

ized features have happened in molecular biology [17].

fragment in 1971 [4].

Undoubtedly the famous physical chemist from the USA, Margaret Dayhoff (1925–1983), the mother and father of bioinformatics, was the key scientist who employed computers and the related software tools in biochemistry [3, 4]. Indeed, it was Dayhoff who understood the importance of computers and

In 1960, Dayhoff as the Associate Director of the National Biomedical Research Foundation began her collaboration with her physicist colleague, Robert S. Ledley, who, like Dayhoff, was interested in employing computers in biomedical sciences

The outcome of their scientific collaboration (Dayhoff-Ledley) in the period of 1958–1962 led to a computer program COMPROTEIN (coded FORTRAN) which was designed for IBM 7090. The software COMPROTEIN (a de novo sequence assembler) was able to determine the primary structure of protein throughout the

During the golden decade between the years 1970 and 1980, the DNA language

was decoded. However, the genetic codes of 64 codons were decoded in 1968 [3, 10]. Sanger's sequencing method of DNA based on "plus and minus" strands was performed 25 years after the recognition of the first protein sequence [3, 11, 12]. 1979 is the historical year for using the first software for Sanger's DNA sequencing method. In the paper published by Rodger Staden in 1979 via the journal of *Nucleic Acids Research*, the applied programs including OVRLAP, XMATCH, and FILINS

During the years of 1980–1990, the application of computational sciences significantly increased. In 1983, the polymerase chain reaction (PCR) was invented by Kary B. Mullis (1944–2019 (https://www.nytimes.com/2019/08/15/science/karyb-mullis-dead.html)). Kary Banks Mullis as an American biochemist invented a valuable molecular method which was based on in vitro synthesis of DNA [14–16]. So, by the discovery of DNA molecules in the 1950s, and in consequence the early application of pro-computers, invention of molecular and sequencing methods, and utilizing Internet services within a short duration, it seems that several revolution-

Although computers and the related software tools were employed since the 1960s in biology, it was in the limited scales. I believe that by the invention of PCR as an in silico-in vitro (dry lab-wet lab) technology and its flying speed as a general molecular biology approach changed the traditional methodologies. By global generalization of PCR, the use of Internet services, computers, and software tools got significant acceleration. In this regard, designing different primers in large and global scales led to progression of in silico studies and appearance of dry labs within the wet labs.

The amino acid one-letter coding system was founded by Dayhoff [3, 8]. Dayhoff and Eck continued their scientific activities by publishing the first edition of the invaluable book entitled *Atlas of Protein Sequence and Structure* in 1965 which involved 65 protein sequences [3, 4, 9]. The fourth edition of *Atlas of Protein Sequence and Structure* which was published in 1969 included more than 300 protein sequences. So, this atlas established the first database of biological sequence [3, 4]. Interestingly, the sequence alignment of biopolymers was started by proteins not DNA molecules. This claim is proven by representing a 12-sequenced DNA

computational methods not only in biology but also in medicine [4].

**2. Biology and computer**

[3, 5, 6].

**4**

Due to this fact, during a very short time, a mass of raw data was obtained by scientists around the world, and these data got stored within different biological databases like the National Center for Biotechnology Information (NCBI) (https:// www.ncbi.nlm.nih.gov/), European Molecular Biology Laboratory (EMBL) (https://www.embl.org/), Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.genome.jp/kegg/), and DNA Data Bank of Japan (DDBJ) (https:// www.ddbj.nig.ac.jp/index-e.html) [18].

At the same time, these giant databases began to give more free software tools, information, and other services. These features have led to establishing 1637 free online databases (http://www.oxfordjournals.org/nar/database/c/) up to now [19].

Today, some databases including The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (https://www.rcsb.org/) serve its global users for free. 3D macromolecular structure data is one of the most popular products which scientists and researchers use for free around the world [20].

Since 1971 when the US data center of RCSB PDB was founded, it provided digital data in biology for its users with open-access policy [20], an opportunity which all the consumers should be grateful for.

All in all, soft biology was founded in the 1960s with a low speed, but it accelerated by the invention of PCR in the 1980s. The PCR invention softened the science of biology throughout Internet services, an occurrence which resulted in progressive in silico studies, dry labs, and software tools.

Today, a biologist is recognized by her/his laptop, Internet connection, and filled USB flash drives with different bioinformatics software tools!

Hence, hard biology got softened by establishing the science of bioinformatics and is continued to be more softened by computational biology!

But the important question is:

"How does biology get more softened in the future?"

### **Conflict of interest**

The authors declare no conflicts of interest.

### **Author details**

Payam Behzadi

Department of Microbiology, College of Basic Sciences, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran

\*Address all correspondence to: behzadipayam@yahoo.com

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Hunter P. Laptop biology. EMBO Reports. 2005;**6**(3):208-210

[2] Penders B, Horstman K, Vos R. Walking the line between lab and computation: The "moist" zone. BioScience. 2008;**58**(8):747-755

[3] Gauthier J, Vincent AT, Charette SJ, Derome N. A brief history of bioinformatics. Briefings in Bioinformatics. 2019;**20**(6):1981-1996

[4] Moody G. Digital Code of Life: How Bioinformatics Is Revolutionizing Science, Medicine, and Business. London: John Wiley & Sons; 2004

[5] Ledley RS. Digital electronic computers in biomedical science. Science. 1959;**130**(3384):1225-1234

[6] November JA. Early biomedical computing and the roots of evidence-based medicine. IEEE Annals of the History of Computing. 2011;**33**(2):9-23

[7] Dayhoff MO, Ledley RS. Comprotein: A computer program to aid primary protein structure determination. In: Proceedings of the December 4-6, 1962, Fall Joint Computer Conference. New York, NY: ACM (Association for Computing Machinery); 1962

[8] International Union of Pure and Applied Chemistry (IUPAC)- the International Union of Biochemistry (IUB) Commission on biochemical nomenclature (CBN). A one-letter notation for amino acid sequences. Tentative rules. European Journal of Biochemistry. 1968;**5**:151-153

[9] Dayhoff MO. Atlas of Protein Sequence and Structure. National Biomedical Research Foundation. Washington, D.C.: Georgetown University Medical Center; 1972

[10] Crick FH. The origin of the genetic code. Journal of Molecular Biology. 1968;**38**(3):367-379

[11] Sanger F, Thompson E. The amino-acid sequence in the glycyl chain of insulin. 1. The identification of lower peptides from partial hydrolysates. Biochemical Journal. 1953;**53**(3):353

[12] Sanger F, Thompson E. The aminoacid sequence in the glycyl chain of insulin. 2. The investigation of peptides from enzymic hydrolysates. Biochemical Journal. 1953;**53**(3):366

[13] Staden R. A strategy of DNA sequencing employing computer programs. Nucleic Acids Research. 1979;**6**(7):2601-2610

[14] Kadri K. Polymerase Chain Reaction (PCR): Principle and Applications. Perspectives on Polymerase Chain Reaction. Croatia: IntechOpen; 2019

[15] Mullis KB, Faloona FA. Specific Synthesis of DNA in Vitro Via a Polymerase-Catalyzed Chain Reaction. Recombinant DNA Methodology. San Diego: Academic Press, Elsevier; 1989. pp. 189-204

[16] Pai-Dhungat J. Kary Mullis— Inventor of PCR. Journal of the Association of Physicians of India. 2019;**67**:96

[17] Bartlett JM, Stirling D. A Short History of the Polymerase Chain Reaction. PCR Protocols. Totowa New Jersy: Humana Press, Springer; 2003. pp. 3-6

[18] Zou D, Ma L, Yu J, Zhang Z. Biological databases for human research. Genomics, Proteomics & Bioinformatics. 2015;**13**(1):55-63

[19] Rigden DJ, Fernández XM. The 27th annual Nucleic Acids Research database

**7**

*Introductory Chapter: From Hard to Soft Biology DOI: http://dx.doi.org/10.5772/intechopen.92572*

issue and molecular biology database collection. Nucleic Acids Research.

2020;**48**(D1):D1-D8

[20] Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, et al. RCSB Protein Data Bank: Biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Research. 2019;**47**(D1):D464-DD74

*Introductory Chapter: From Hard to Soft Biology DOI: http://dx.doi.org/10.5772/intechopen.92572*

issue and molecular biology database collection. Nucleic Acids Research. 2020;**48**(D1):D1-D8

[20] Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, et al. RCSB Protein Data Bank: Biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Research. 2019;**47**(D1):D464-DD74

**6**

*Computational Biology and Chemistry*

[1] Hunter P. Laptop biology. EMBO

[10] Crick FH. The origin of the genetic code. Journal of Molecular Biology.

[12] Sanger F, Thompson E. The aminoacid sequence in the glycyl chain of insulin. 2. The investigation of peptides from enzymic hydrolysates. Biochemical

[11] Sanger F, Thompson E. The amino-acid sequence in the glycyl chain of insulin. 1. The identification of lower peptides from partial hydrolysates. Biochemical Journal.

1968;**38**(3):367-379

1953;**53**(3):353

Journal. 1953;**53**(3):366

1979;**6**(7):2601-2610

pp. 189-204

2019;**67**:96

pp. 3-6

[13] Staden R. A strategy of DNA sequencing employing computer programs. Nucleic Acids Research.

[14] Kadri K. Polymerase Chain Reaction (PCR): Principle and Applications. Perspectives on Polymerase Chain Reaction. Croatia: IntechOpen; 2019

[15] Mullis KB, Faloona FA. Specific Synthesis of DNA in Vitro Via a

[16] Pai-Dhungat J. Kary Mullis— Inventor of PCR. Journal of the Association of Physicians of India.

[17] Bartlett JM, Stirling D. A Short History of the Polymerase Chain Reaction. PCR Protocols. Totowa New Jersy: Humana Press, Springer; 2003.

[18] Zou D, Ma L, Yu J, Zhang Z. Biological databases for human research. Genomics, Proteomics & Bioinformatics. 2015;**13**(1):55-63

[19] Rigden DJ, Fernández XM. The 27th annual Nucleic Acids Research database

Polymerase-Catalyzed Chain Reaction. Recombinant DNA Methodology. San Diego: Academic Press, Elsevier; 1989.

[2] Penders B, Horstman K, Vos R. Walking the line between lab and computation: The "moist" zone. BioScience. 2008;**58**(8):747-755

[3] Gauthier J, Vincent AT, Charette SJ, Derome N. A brief history of bioinformatics. Briefings in Bioinformatics.

[4] Moody G. Digital Code of Life: How Bioinformatics Is Revolutionizing Science, Medicine, and Business. London: John Wiley & Sons; 2004

[5] Ledley RS. Digital electronic computers in biomedical science. Science. 1959;**130**(3384):1225-1234

[6] November JA. Early biomedical computing and the roots of evidence-based medicine. IEEE Annals of the History of Computing.

[8] International Union of Pure and Applied Chemistry (IUPAC)- the International Union of Biochemistry (IUB) Commission on biochemical nomenclature (CBN). A one-letter notation for amino acid sequences. Tentative rules. European Journal of

Biochemistry. 1968;**5**:151-153

[9] Dayhoff MO. Atlas of Protein Sequence and Structure. National Biomedical Research Foundation. Washington, D.C.: Georgetown University Medical Center; 1972

[7] Dayhoff MO, Ledley RS. Comprotein: A computer program to aid primary protein structure determination. In: Proceedings of the December 4-6, 1962, Fall Joint Computer Conference. New York, NY: ACM (Association for Computing

Reports. 2005;**6**(3):208-210

**References**

2019;**20**(6):1981-1996

2011;**33**(2):9-23

Machinery); 1962

Section 2

Wet Labs and Dry Labs: From

In Vitro to In Silico Studies

**9**

Section 2
