Biology is designed for multi-semester biology courses for science majors. It is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand. To meet the needs of today’s instructors and students, some content has been strategically condensed while maintaining the overall scope and coverage of traditional texts for this course. Instructors can customize the book, adapting it to the approach that works best in their classroom. Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand—and apply—key concepts.

By the end of this section, you will be able to:Explain systems biologyDescribe a proteomeDefine protein signature

This course focuses on feedback control mechanisms that living organisms implement at the molecular level to execute their functions, with emphasis on techniques to design novel systems with prescribed behaviors. Students will learn how biological functions can be understood and designed using notions from feedback control.

The course focuses on casting contemporary problems in systems biology and functional genomics in computational terms and providing appropriate tools and methods to solve them. Topics include genome structure and function, transcriptional regulation, and stem cell biology in particular; measurement technologies such as microarrays (expression, protein-DNA interactions, chromatin structure); statistical data analysis, predictive and causal inference, and experiment design. The emphasis is on coupling problem structures (biological questions) with appropriate computational approaches.

This subject describes and illustrates computational approaches to solving problems in systems biology. A series of case-studies will be explored that demonstrate how an effective match between the statement of a biological problem and the selection of an appropriate algorithm or computational technique can lead to fundamental advances. The subject will cover several discrete and numerical algorithms used in simulation, feature extraction, and optimization for molecular, network, and systems models in biology.

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas.

This course will focus on understanding aspects of modern technology displaying exponential growth curves and the impact on global quality of life through a weekly updated class project integrating knowledge and providing practical tools for political and business decision-making concerning new aspects of bioengineering, personalized medicine, genetically modified organisms, and stem cells. Interplays of economic, ethical, ecological, and biophysical modeling will be explored through multi-disciplinary teams of students, and individual brief reports.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Host-microbiome interactions are a critical component of host health, and plants have a particularly complex relationship with their microbiomes. Understanding these functional relationships will allow us to predict, and even influence, host fitness. Many ‘-omics’ techniques have been developed, and each is a powerful tool solo, but combining them opens the door to a more holistic, systems-level understanding. This strategy, called holo-omics, requires careful experimental design and faces several challenges as a field. First, it currently lacks well-tested analytical frameworks. Second, there is a need for freely available, specialized bioinformatics tools, as most focus on just one data source and don't integrate host and microbe data. Lastly, the heterogeneous nature of holo-omics data requires a wide range of expertise - including plant biologists, microbe experts, statisticians, and computational biologists..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This class is a project-based introduction to the engineering of synthetic biological systems. Throughout the term, students develop projects that are responsive to real-world problems of their choosing, and whose solutions depend on biological technologies. Lectures, discussions, and studio exercises will introduce (1) components and control of prokaryotic and eukaryotic behavior, (2) DNA synthesis, standards, and abstraction in biological engineering, and (3) issues of human practice, including biological safety; security; ownership, sharing, and innovation; and ethics. Enrollment preference is given to freshmen.
This subject was originally developed and first taught in Spring 2008 by Drew Endy and Natalie Kuldell. Many of Drew’s materials are used in this Spring 2009 version, and are included with his permission.
This OCW Web site is based on the OpenWetWare class Wiki, found at OpenWetWare: 20.020 (S09)

This book is an introduction to the language of systems biology, which is spoken among many disciplines, from biology to engineering. Authors Thomas Sauter and Marco Albrecht draw on a multidisciplinary background and evidence-based learning to facilitate the understanding of biochemical networks, metabolic modeling and system dynamics.

Their pedagogic approach briefly highlights core ideas of concepts in a broader interdisciplinary framework to guide a more effective deep dive thereafter. The learning journey starts with the purity of mathematical concepts, reveals its power to connect biological entities in structure and time, and finally introduces physics concepts to tightly align abstraction with reality.

This workbook is all about self-paced learning, supports the flipped-classroom concept, and kick-starts with scientific evidence on studying. Each chapter comes with links to external YouTube videos, learning checklists, and Integrated real-world examples to gain confidence in thinking across scientific perspectives. The result is an integrated approach that opens a line of communication between theory and application, enabling readers to actively learn as they read.

This overview of capturing and analyzing the behavior of biological systems will interest adherers of systems biology and network analysis, as well as related fields such as bioinformatics, biology, cybernetics, and data science.

This course provides a foundation in the following four areas: evolutionary and population genetics; comparative genomics; structural genomics and proteomics; and functional genomics and regulation.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Roundup is the most widely used non-selective herbicide, but it’s also one of the most controversial on the market. Much evidence about Roundup's safety is based on toxicity tests that, despite being outdated, are routinely used by regulators and say little about the long-term, sublethal effects of Roundup or its active ingredient glyphosate. Now, a new study has taken a systems biology approach to examine the effects of Roundup on organisms at at the genomic and fitness level. Daphnia are not a Roundup target but are exposed to the herbicide through run-off from farmlands and they are central to aquatic food webs. In the lab, Daphnia were exposed to the regulatory threshold concentration of glyphosate and Roundup. Researchers found that chronic exposure to either chemical had highly detrimental effects including embryonic developmental failure, DNA damage, and signaling interference. Daphnia also showed changes in their microbiome and disruptions in metabolism..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Solid organ transplant recipients need immunosuppressive therapy for the rest of their lives and have more distinct virus populations in their microbiome than people without suppressed immune systems. But we do not yet know if, or how much, the donor’s virome impacts the recipient’s virome, particularly in parts of the body other than the transplanted organ. To narrow this gap, a recent study applied a data modeling approach to the viral communities in the airway and plasma of lung transplant recipients. Differences between plasma and airway viromes increased during the first year after implantation, but the viromes from the same body site and in different patients became more similar over time. Time after transplantation was significantly associated with virome composition variance for airway samples but not plasma samples..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This is a seminar based on research literature. Papers covered are selected to illustrate important problems and approaches in the field of computational and systems biology, and provide students a framework from which to evaluate new developments.
The MIT Initiative in Computational and Systems Biology (CSBi) is a campus-wide research and education program that links biology, engineering, and computer science in a multidisciplinary approach to the systematic analysis and modeling of complex biological phenomena. This course is one of a series of core subjects offered through the CSB Ph.D. program, for students with an interest in interdisciplinary training and research in the area of computational and systems biology.