In the realm of modern software development, Git and GitHub stand as two pillars supporting collaborative coding efforts. Git, a distributed version control system, revolutionized the way developers manage and track changes in their projects. GitHub, on the other hand, serves as a platform for hosting Git repositories and facilitating collaboration among developers worldwide.

Let's delve into these two indispensable tools and explore their significance in the world of programming!

What is Git?

Git, developed by Linus Torvalds in 2005, is a distributed version control system (VCS) designed to handle everything from small to very large projects with speed and efficiency. Unlike centralized version control systems, Git stores a full copy of the project's history on every developer's local machine.

This distributed nature grants developers the freedom to work offline, experiment with different changes, and collaborate seamlessly with others without being tethered to a central server.

• Key Concepts of Git:

1. Repositories: Git operates within repositories, which are essentially folders that Git tracks for changes. These repositories can be local or hosted on a remote server.

2. Commits: A commit represents a snapshot of changes made to the repository at a specific point in time. Developers create commits to save their work and provide a meaningful description of the changes made.

3. Branches: Branches in Git allow developers to diverge from the main line of development and work on features or fixes independently. Branches provide isolation, enabling multiple developers to work on different parts of a project simultaneously.

4. Merging: Merging is the process of integrating changes from one branch into another. Git automates much of the merging process, but conflicts can arise that require manual resolution.

Command Line Playlist by Elzero - Arabic

What is GitHub?

GitHub, founded in 2008, is a web-based platform built around Git that provides hosting for software development and version control using Git.

It offers a wide range of collaboration features such as bug tracking, feature requests, task management, and wikis for every project. GitHub has become the de facto platform for open-source projects, enabling developers to share code, contribute to others' projects, and collaborate with peers around the globe.

• Key Features of GitHub:

1. Repositories: GitHub hosts millions of repositories covering various programming languages and projects. Each repository has its own URL and can be accessed and cloned by anyone.

2. Pull Requests: Pull requests are proposals for changes submitted by a developer who wants to merge their code into the main branch of a repository. They facilitate code review and discussion among team members before changes are integrated.

3. Issues: GitHub's issue tracker allows developers to report bugs, request features, and discuss ideas related to a project. Issues can be labeled, assigned, and prioritized to streamline project management.

4. Collaboration: GitHub fosters collaboration through features like project boards, wikis, and team permissions. Developers can work together seamlessly, whether they're in the same room or on opposite sides of the globe.

GitHub Playlist by Elzero - Arabic

Conclusion

Git and GitHub have revolutionized the way software is developed, making collaboration easier and more efficient than ever before.

By mastering these tools, developers gain the ability to manage projects effectively, track changes meticulously, and collaborate seamlessly with peers.

Whether you're a seasoned developer or just starting your coding journey, understanding Git and GitHub is essential for success in the modern software development landscape.

 🌐 Exploring the World Wide Web 🌐

Exploring the World Wide Web, Amr Bedir Blog

Have you ever wondered about the backbone of our modern digital age? I'd like to delve into the fascinating realm of the World Wide Web aka (WWW) and its profound impact on our lives. 👀

The World Wide Web, often simply referred to as the Web, is a global information space where documents and other web resources are identified by Uniform Resource Locators (URLs) and can be accessed via the Internet. It was developed in the late 1980s and early 1990s by Sir: Tim Berners-Lee, a British computer scientist, and has since revolutionized the way we communicate, collaborate, and access information.

Key components of the World Wide Web include:

1️⃣ Hypertext Markup Language (HTML): The standard markup language for creating web pages and web applications. HTML allows for the structuring of content on a web page through the use of tags and attributes.

2️⃣ Hyperlinks: These are the clickable connections that allow users to navigate between web pages. Hyperlinks are fundamental to the interconnected nature of the Web, enabling seamless browsing across different sites and resources.

3️⃣ Web Browsers: Software applications that allow users to access and view web pages. Popular web browsers include Google Chrome, Mozilla Firefox, and Safari, each offering unique features and functionalities to enhance the browsing experience.

4️⃣ Web Servers: These are computers that store and serve web pages to users upon request. Web servers host websites and web applications, making them accessible to visitors from anywhere.

The World Wide Web has transformed the way we communicate, conduct business, and access information. It has facilitated global connectivity, empowered individuals and organizations to share knowledge and resources, and paved the way for innovations in various fields, including education, commerce, and entertainment.

Naaaah, As we continue to navigate the digital landscape, let's reflect on the profound impact of the World Wide Web and its ongoing evolution in shaping our interconnected world. Ready? 👀

- For future posts, follow on LinkedIn: https://www.linkedin.com/in/amrbedir/

In the age of information, Google has become more than just a search engine—it's a gateway to a universe of knowledge, a treasure trove of information waiting to be uncovered. However, not everyone knows that beneath the familiar search bar lies a secret toolkit that can enhance your search experience exponentially. These are the Google search operators, a collection of commands and symbols that allow you to fine-tune your searches and uncover precisely what you're looking for. In this article, we'll delve into the world of Google search operators and explore how to harness their power to become a more effective researcher.

What are Google Search Operators?

Google search operators are special commands and symbols that you can use within your search queries to refine and tailor your search results. They act as shortcuts to modify how Google's search engine retrieves and displays information. Whether you're a student conducting research, a professional seeking specific data, or simply an information enthusiast, these operators can help you sift through the overwhelming sea of search results and find precisely what you need.

Basic Google Search Operators:

Quotation Marks (" "): Placing words within quotation marks instructs Google to search for that exact phrase. This is incredibly useful when you're looking for specific quotes, song lyrics, or a sequence of words.

Minus Sign (-): Use the minus sign to exclude certain words from your search results. For instance, if you're searching for recipes but want to exclude any results with "gluten," you can type "recipes -gluten."

Asterisk (*): The asterisk is a wildcard that can be used to replace words in a phrase. This is handy when you're trying to remember a phrase but can't recall all the words. For example, "a * in time saves nine" will help you find the full adage.

Advanced Google Search Operators:

Site (site:URL): If you're looking for information on a specific website, you can use the site operator. For example, "technology site:wired.com" will only show results from Wired's website.

Filetype (filetype:extension): If you're in search of a specific type of file, such as a PDF or PowerPoint presentation, using the filetype operator can be invaluable. For example, "climate change report filetype:pdf" will narrow down your results to PDF files related to climate change reports.

Related (related:URL): To find websites similar to a particular URL, use the related operator. For instance, "related:nytimes.com" will give you websites that are similar in content to The New York Times.

Define (define:word): If you're looking for a quick definition, use the define operator. "define:serendipity" will give you a concise definition of the word.

OR (OR or |): When you want to search for multiple terms simultaneously, you can use the OR operator. For example, "history of art OR sculpture" will yield results related to both art history and sculpture.

Combining Operators for Precision:

The true power of Google search operators shines when you combine them. Suppose you're researching climate change impacts on wildlife. You could search using a query like "climate change effects on wildlife site:nationalgeographic.com filetype:pdf." This search would give you PDF files from National Geographic specifically addressing the impacts of climate change on wildlife.

Conclusion:

Google search operators are the hidden gems of online research. By mastering these commands and symbols, you can navigate the vast sea of information more efficiently and extract exactly the data you need. Whether you're a student, professional, or curious individual, these tools empower you to become a more effective and precise researcher. So, next time you embark on an information quest, remember to utilize Google search operators to unlock the full potential of your search engine experience.

Abstract:

The question of whether thinking consumes body energy has intrigued researchers for decades. The brain is known to be a metabolically active organ, consuming a significant proportion of the body's energy. However, the exact relationship between cognitive processes and energy expenditure remains a complex and multifaceted topic. This article explores the current state of knowledge on the energy demands of thinking and cognitive activities, drawing from a wide range of studies in neuroscience, physiology, and psychology. By delving into the metabolic processes underlying cognition, this paper sheds light on the potential impact of thinking on overall body energy consumption.

Introduction:

The brain is a marvel of evolution, orchestrating complex cognitive processes that define human intelligence and consciousness. This unique function demands a continuous supply of energy. The relationship between cerebral metabolism and cognitive function has fascinated researchers and raised the question: does thinking consume body energy? To address this question, we delve into the intricate metabolic mechanisms in the brain and explore how cognitive tasks may impact energy expenditure.

The Metabolic Basis of Brain Activity:

The brain accounts for only about 2% of the body's weight, yet it consumes approximately 20% of the body's total energy at rest. This high energy demand is mainly due to the ongoing maintenance of ion gradients, neurotransmitter synthesis, and the energy-intensive process of action potential generation and propagation. Glucose is the primary fuel for brain activity, and its utilization is tightly regulated to support the brain's dynamic energy needs.

Cognitive Tasks and Energy Expenditure:

Several studies have sought to measure the energy consumption associated with various cognitive tasks. Functional neuroimaging techniques, such as fMRI and PET scans, have provided valuable insights into regional brain activation during thinking processes. While these studies suggest increased energy consumption in specific brain regions during cognitive tasks, it is challenging to quantify precisely the additional energy expenditure associated with thinking alone.

Mental Effort and Energy Allocation:

Some researchers argue that specific cognitive activities, especially those requiring intense mental effort or concentration, may lead to an increase in overall energy consumption. Mental arithmetic, problem-solving, or engaging in complex decision-making processes are believed to elevate energy expenditure compared to passive or routine tasks. However, the magnitude and duration of these effects are not yet fully understood.

Factors Influencing Brain Energy Consumption:

Several factors may influence the relationship between thinking and energy expenditure. Individual differences, such as cognitive abilities and brain structure, might impact energy utilization during cognitive tasks. Additionally, emotional states, stress, and mental fatigue may also contribute to varying energy demands in different thinking scenarios.

Brain Energy Depletion and Cognitive Fatigue:

Prolonged and intensive cognitive tasks may lead to cognitive fatigue, characterized by reduced attention, impaired decision-making, and decreased cognitive performance. Some evidence suggests that cognitive fatigue might be associated with localized brain energy depletion or changes in neurotransmitter balance. However, more research is needed to establish a direct causal link between cognitive fatigue and brain energy metabolism.

Future Directions and Implications:

Advancements in neuroimaging techniques and brain-computer interface technology hold promise for further exploring the relationship between thinking and energy expenditure. Understanding the energy demands of cognitive processes could have implications for optimizing mental performance, managing cognitive fatigue, and promoting overall brain health.

Conclusion:

The question of whether thinking consumes body energy remains an ongoing area of investigation. The brain's metabolic demands are undeniably substantial, but the exact contribution of cognitive tasks to overall energy expenditure remains complex and challenging to quantify. Further interdisciplinary research is essential to unravel the intricate interplay between cerebral metabolism and cognitive function, ultimately shedding light on the profound relationship between the mind and body.

Abstract: 

Embedded systems play a pivotal role in our modern society, seamlessly integrating hardware and software to perform specific tasks with efficiency and precision. This article provides a comprehensive overview of embedded systems, highlighting their significance, advancements, and diverse applications. delve into the fundamental concepts, architectures, design considerations, and programming methodologies associated with embedded systems. Moreover, we explore recent advancements and emerging trends that are shaping the future of embedded systems, while discussing their impact on various industries and everyday life. This article aims to provide readers with an insightful understanding of embedded systems and their potential for driving innovation in the digital era.

Introduction: 

Embedded systems, often referred to as the "hidden intelligence" of various devices and machines, have become an integral part of our modern world. These systems are designed to perform specific tasks with precision, reliability, and real-time response. This section provides an overview of embedded systems, their definition, and their importance in today's society.

Fundamental Concepts of Embedded Systems: 

In this section, we discuss the foundational concepts of embedded systems, including their basic architecture, components, and design considerations. We explore the distinction between general-purpose computing systems and embedded systems, emphasizing the specialized nature of the latter. Key topics covered include processors, memory, input/output interfaces, and power management.

Embedded Systems Design: 

Designing an embedded system involves a systematic approach to ensure optimal performance and functionality. We explore the design process, including requirements analysis, system specification, hardware and software partitioning, and prototyping. Furthermore, we discuss various design methodologies, such as top-down, bottom-up, and object-oriented approaches, along with their advantages and limitations.

Programming Embedded Systems: 

Programming embedded systems presents unique challenges due to resource constraints and real-time requirements. This section provides an overview of programming languages, tools, and techniques commonly employed in embedded system development. We delve into low-level programming languages like C and assembly, as well as high-level languages and frameworks. Additionally, we discuss debugging and testing methodologies specific to embedded systems.

Advancements in Embedded Systems:

The rapid advancement of technology has led to significant improvements in embedded systems. This section highlights recent advancements, including the rise of Internet of Things (IoT), machine learning, artificial intelligence, and edge computing in the realm of embedded systems. We discuss how these advancements have expanded the capabilities of embedded systems, enabling innovative applications in various fields.

Applications of Embedded Systems: 

Embedded systems have a vast array of applications across industries. In this section, we explore how embedded systems are utilized in domains such as automotive, healthcare, aerospace, consumer electronics, industrial automation, and smart homes. We discuss specific examples, such as autonomous vehicles, wearable medical devices, drones, and smart appliances, showcasing the diverse range of applications enabled by embedded systems.

Emerging Trends and Future Perspectives: 

Looking ahead, this section discusses emerging trends and future directions in the field of embedded systems. We examine the impact of technologies like edge computing, cybersecurity, robotics, and embedded vision on the evolution of embedded systems. Furthermore, we explore the potential challenges and opportunities that lie ahead, highlighting the need for interdisciplinary collaboration and continued research and development.

Conclusion: 

Embedded systems have become indispensable in our increasingly interconnected and digital world. This article provided a comprehensive overview of embedded systems, covering fundamental concepts, design considerations, programming methodologies, advancements, applications, and future trends. By understanding the intricacies of embedded systems, researchers, engineers, and enthusiasts can unlock the full potential of this technology, driving innovation and shaping the future of various industries and everyday life.

User References:

• "Embedded Systems: Introduction to ARM Cortex-M Microcontrollers" by Jonathan Valvano
• "Embedded Systems: Real-Time Interfacing to ARM Cortex-M Microcontrollers" by Jonathan Valvano
• "Embedded Systems: Design, Analysis and Verification" by Eyal Zohar
• "Embedded Systems: Architecture, Programming and Design" by Raj Kamal
• "Embedded Systems: A Contemporary Design Tool" by James K. Peckol
• "Programming Embedded Systems: With C and GNU Development Tools" by Michael Barr and Anthony Massa
• "Embedded Systems Design: An Introduction to Processes, Tools, and Techniques" by Arnold S. Berger
• "The Art of Designing Embedded Systems" by Jack Ganssle
• "Building Embedded Systems: Programmable Hardware" by Changyi Gu
• "Embedded Systems: Hardware, Design and Implementation" by Krzysztof Iniewski

Abstract: 

Robotics has emerged as a transformative field of study, bringing together engineering, computer science, and artificial intelligence. 

This article explores the advancements, applications, and impact of robotics on various industries and its potential to enhance human capabilities. also delves into robotics's challenges and future prospects, offering a comprehensive overview of this rapidly evolving field.

Introduction:

In recent years, robotics has gained significant attention due to its potential to revolutionize industries and augment human capabilities. With advancements in technology, robotics has moved beyond the realm of science fiction and is now becoming an integral part of our lives. 

This article presents an overview of the current state of robotics, highlighting its applications, impact, and future prospects.

Advancements in Robotics:

2.1 Hardware Innovations:

Sensing and Perception: Improvements in sensors enable robots to perceive and interact with the environment, facilitating tasks in unstructured and dynamic settings.

Actuators and Manipulation: Advanced robotic arms and grippers offer precise and dexterous manipulation, allowing robots to handle complex objects and perform delicate tasks.

Mobility and Locomotion: Novel locomotion mechanisms, such as legged robots and drones, enable robots to navigate diverse terrains and perform tasks in challenging environments.

2.2 Artificial Intelligence and Machine Learning:

Cognitive Abilities: Integration of AI and machine learning algorithms empowers robots with decision-making capabilities, adaptability, and learning from human interactions.

Computer Vision: Computer vision algorithms enable robots to perceive and interpret visual information, facilitating object recognition, tracking, and scene understanding.

Natural Language Processing: Robots with natural language processing capabilities can understand and respond to human commands, enabling seamless human-robot interaction.

Applications of Robotics:

3.1 Manufacturing and Industrial Automation:

Collaborative Robotics: Robots working alongside humans in manufacturing processes enhance efficiency, safety, and productivity.

Assembly and Quality Control: Robots excel in repetitive tasks, improving accuracy and consistency in assembly lines and quality control procedures.

Logistics and Warehousing: Autonomous mobile robots streamline order fulfillment and material handling, optimizing warehouse operations.

3.2 Healthcare and Medicine:

Surgical Robotics: Minimally invasive robotic surgery systems provide surgeons with enhanced precision, dexterity, and visualization, improving patient outcomes.

Rehabilitation and Assistive Robotics: Robotic exoskeletons and prosthetics aid in physical therapy and assist individuals with mobility impairments, enabling greater independence.

3.3 Agriculture and Food Industry:

Precision Agriculture: Robots equipped with sensors and AI assist in crop monitoring, automated irrigation, and targeted pesticide application, optimizing yield and resource usage.

Harvesting and Sorting: Autonomous robots efficiently harvest crops and perform sorting tasks, reducing labor-intensive processes and enhancing productivity.

3.4 Exploration and Hazardous Environments:

Space Exploration: Robots and rovers play a vital role in space exploration, conducting scientific experiments, and gathering data in harsh and distant environments.

Disaster Response: Robots can be deployed in search and rescue missions, hazardous material handling, and structural inspections, mitigating risks to human lives.

Impact and Challenges:

4.1 Economic Impact: 

Robotics revolutionizes industries, creating new job opportunities, boosting productivity, and improving competitiveness. However, there are concerns about job displacement and the need for upskilling the workforce.

4.2 Ethical Considerations: 

The rise of autonomous robots raises ethical questions regarding accountability, privacy, and the impact on human values. Addressing these concerns is crucial for the responsible development and deployment of robotic systems.

4.3 Human-Robot Interaction: 

Designing intuitive interfaces and establishing effective human-robot collaboration is essential for user acceptance and seamless integration of robots into society.

Future Prospects:

The future of robotics holds tremendous potential. Areas of research include soft robotics, swarm robotics, bio-inspired designs, and human-robot symbiosis. 

Progress in these areas will enable robots to tackle more complex tasks, interact naturally with humans, and contribute to the betterment of society.

Conclusion:

Robotics has transformed industries and expanded the possibilities of what machines can achieve. 

From manufacturing to healthcare, agriculture to space exploration, robotics has proven its ability to enhance productivity, improve safety, and augment human potential. However, challenges such as ethics, human-robot interaction, and workforce adaptation need to be addressed for the responsible and beneficial integration of robots into our daily lives. With ongoing advancements and research, robotics is poised to shape a promising future where humans and robots collaborate to create a more efficient, sustainable, and technologically advanced society.

Used References:

Research Journals:

• IEEE Transactions on Robotics
• Robotics and Autonomous Systems
• International Journal of Robotics Research
• Journal of Field Robotics
• Autonomous Robots

Conferences and Proceedings:

• IEEE International Conference on Robotics and Automation (ICRA)
• Robotics: Science and Systems (RSS)
• International Symposium on Robotics Research (ISRR)
• International Conference on Intelligent Robots and Systems (IROS)
• Robotics and Automation Society (RAS) conferences

Organizations and Institutions:

• Robotics Industries Association (RIA)
• International Federation of Robotics (IFR)
• Association for the Advancement of Artificial Intelligence (AAAI)
• Robotics and Artificial Intelligence Society (RAICS)
• Robotics and Automation Society (RAS)

Online Platforms and Communities:

• RobotShop Community: Offers forums, tutorials, and resources for robotics enthusiasts.
• ROS (Robot Operating System) Wiki: Provides documentation and tutorials for the open-source robotics framework.
• GitHub: Explore repositories related to robotics projects and code examples.
• Robotics Stack Exchange: An online community for asking and answering robotics-related questions.

Books and Publications:

• "Introduction to Autonomous Robots" by Nikolaus Correll, Bradley Hayes, and Ronald R. Petrick.
• "Robot Modeling and Control" by Mark W. Spong, Seth Hutchinson, and M. Vidyasagar.
• "Robotics: Modelling, Planning and Control" by Bruno Siciliano and Lorenzo Sciavicco.
• "Probabilistic Robotics" by Sebastian Thrun, Wolfram Burgard, and Dieter Fox.
• "Robotics: Discover the Science and Technology of the Future" by Kathy Ceceri.

 

Advancing Biological Discovery through Bioinformatics: Unveiling the Power of Data Integration and Computational Analysis

Abstract: 

Bioinformatics has emerged as a transformative discipline at the intersection of biology, computer science, and statistics. It utilizes computational tools and techniques to extract valuable insights from vast amounts of biological data, enabling researchers to unravel complex biological phenomena and accelerate scientific discovery. 

This article provides an overview of bioinformatics, highlighting its essential role in genomics, proteomics, and systems biology. explores the various applications of bioinformatics, including sequence analysis, structural biology, comparative genomics, and drug discovery. 

Additionally, this article discusses the challenges and future directions of bioinformatics, underscoring the potential impact of this interdisciplinary field on our understanding of life itself.

Introduction:

The advent of high-throughput technologies, such as next-generation sequencing, has led to an exponential increase in the generation of biological data. 

Bioinformatics has emerged as a vital field to handle, analyze, and interpret this vast amount of information. By integrating computational methods, statistical analysis, and biological knowledge, bioinformatics has revolutionized biological research, offering unprecedented opportunities to explore the intricacies of living systems.

Bioinformatics in Genomics:

Genomics, the study of an organism's entire set of genes, has been revolutionized by bioinformatics. Sequence alignment algorithms, gene prediction methods, and functional annotation tools enable the identification and characterization of genes, regulatory elements, and non-coding RNAs. 

Comparative genomics allows the study of evolutionary relationships between species, aiding in the identification of conserved regions and the discovery of novel genes.

Bioinformatics in Proteomics:

Proteomics involves the large-scale study of proteins, their structures, functions, and interactions within biological systems. 

Bioinformatics plays a crucial role in protein structure prediction, protein-protein interaction networks, and the analysis of post-translational modifications. By integrating proteomics data with other biological datasets, bioinformatics facilitates the identification of potential drug targets and biomarkers for disease diagnosis.

Bioinformatics in Systems Biology:

Systems biology aims to understand biological processes as interconnected networks of molecules and their interactions. 

Bioinformatics tools enable the integration of multi-omics data, such as genomics, transcriptomics, proteomics, and metabolomics, to construct comprehensive models of biological systems. These models can simulate complex biological phenomena, leading to a deeper understanding of cellular processes, disease mechanisms, and the discovery of novel therapeutic interventions.

Challenges in Bioinformatics:

Despite its tremendous potential, bioinformatics faces several challenges. The exponential growth of biological data requires scalable and efficient computational methods for data storage, retrieval, and analysis. Standardization of data formats, development of robust algorithms, and advancements in machine learning techniques are crucial to handle the complexities inherent in biological data. Furthermore, ethical considerations, data privacy, and reproducibility of results are significant concerns that must be addressed.

Future Directions:

The future of bioinformatics holds great promise. The integration of diverse data types, including single-cell genomics, metagenomics, and epigenomics, will provide a more comprehensive understanding of biological systems. 

Advancements in artificial intelligence and deep learning algorithms will enable the analysis of complex datasets, leading to the discovery of novel patterns and relationships. Furthermore, the application of bioinformatics in personalized medicine and precision agriculture will revolutionize healthcare and food production, respectively.

Conclusion:

Bioinformatics has become an indispensable tool in modern biology, empowering scientists to make sense of the deluge of biological data. 

Its applications span genomics, proteomics, and systems biology, providing valuable insights into the complexities of life. As bioinformatics continues to evolve, it holds the potential to revolutionize our understanding of biology, shape personalized medicine, and address global challenges in fields such as agriculture and environmental conservation. With ongoing advancements in computational power, data integration, and analytical methods, bioinformatics is poised to unlock the secrets of life's most intricate mechanisms.

Used references:

• Aluru, S. (Ed.). (2018). Handbook of Computational Molecular Biology. Chapman and Hall/CRC.
• Baxevanis, A. D., & Ouellette, B. F. (Eds.). (2004). Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins. John Wiley & Sons.
• Lesk, A. M. (2017). Introduction to Bioinformatics. Oxford University Press.
• Pevsner, J. (2015). Bioinformatics and Functional Genomics. John Wiley & Sons.
• Mount, D. W. (2004). Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press.
• Durbin, R., Eddy, S. R., Krogh, A., & Mitchison, G. (1998). Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press.
• Bourne, P. E., & Weissig, H. (Eds.). (2003). Structural Bioinformatics. John Wiley & Sons.
• Markowetz, F. (2019). Data Science for Biologists. Cambridge University Press.
• Jensen, L. J., & Bateman, A. (2013). Bioinformatics: An Introduction. John Wiley & Sons.
• Salzberg, S. L. (2019). Bioinformatics: Introduction and Methods. Springer.