This interdisciplinary course provides a hands-on approach to students in the topics of bioinformatics and proteomics. Lectures and labs cover sequence analysis, microarray expression analysis, Bayesian methods, control theory, scale-free networks, and biotechnology applications. Designed for those with a computational and/or engineering background, it will include current real-world examples, actual implementations, and engineering design issues. Where applicable, engineering issues from signal processing, network theory, machine learning, robotics and other domains will be expounded upon.

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 teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system design with the ability to carry out a significant independent project.
This course was offered as part of the Singapore-MIT Alliance (SMA) program as course number SMA 5304.

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:

"Breast cancer is the most commonly diagnosed form of cancer, and it is also one of the most deadly. People who take progesterone for hormone replacement therapy or contraceptive purposes may be particularly at risk. A new study showed that disruption of the intricate balance between two cell signaling cascades may be at least partly to blame. Progesterone is thought to trigger cellular responses by binding to either classic nuclear receptors or non- classic membrane receptors. Researchers showed that the genes CCM1-3 (which form the CCM signaling complex) mediate the crosstalk between the signaling pathways associated with these two receptor types. The signaling network involving progesterone, the CCM complex, and membrane and nuclear receptors relies on an intricate feedback system to maintain homeostasis, indicating that excess progesterone can throw it out of balance..."

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

This course covers the algorithmic and machine learning foundations of computational biology combining theory with practice. We cover both foundational topics in computational biology, and current research frontiers. We study fundamental techniques, recent advances in the field, and work directly with current large-scale biological datasets.

With the growing availability and lowering costs of genotyping and personal genome sequencing, the focus has shifted from the ability to obtain the sequence to the ability to make sense of the resulting information. This course is aimed at exploring the computational challenges associated with interpreting how sequence differences between individuals lead to phenotypic differences in gene expression, disease predisposition, or response to treatment.

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:

"Understanding how microbes relate in complicated ecosystems is important. Medicine, biotechnology, and environmental ecology depend on identifying the types and proportions of bacteria in a given sample. Metaproteomics has emerged as a powerful analytical tool for studying the protein content of complex microbial samples. Unfortunately, database limitations such as unequal coverage of life branches can influence protein inferences, leading to misidentification of species. Thus, for diverse samples, more robust methods are needed to fully understand the diversity of microorganisms present in biological samples. Now, researchers have developed a new method to identify the biomass contribution of an organism. The technique, called “phylopeptidomics,” uses mathematical models and phylogenetic relationships to evaluate the peptide signatures present in a sample..."

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:

"A new method for identifying post-translational modifications in proteins promises to cut biomedical researchers’ workload in half. Enabling multiple affinity enrichment procedures to be run in parallel, the one-pot method yields the same search results as traditional methods in less time and from less tissue. As proteomics researchers know well, identifying post-translational modifications in biological samples can be tedious. Enriching samples with target modifications, such as the attachment of acetyl , succinyl or methyl groups to amino acid residues, and matching experimental data with catalogued results involves numerous steps. And the work load is only getting bigger. With exploding interest in how multiple modifications are linked across the vast proteome , the amount of time and the amount of sample required for exploration are skyrocketing in proportion. But with the new one-pot enrichment method, that could soon change..."

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:

"A new study suggests that transferring gut microbes from aged to young adult mice has measurable effects on parts of the central nervous system, highlighting the importance of the gut–brain axis in aging. Researchers performed fecal transplants from aged or age-matched donors to younger adult mice. The two groups showed significant differences in their microbial profiles. After transplantation, young adult recipients showed no significant changes in markers of anxiety, explorative behavior, or locomotor activity. But recipients did show impaired spatial learning and memory, as measured by a maze test. These changes were paralleled by alterations in the expression of proteins associated with synaptic plasticity and neurotransmission and changes in microglial cells in the hippocampus — the learning and memory center of the brain..."

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

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 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:

"Glioblastomas are deadly, malignant brain tumors. Even with current treatment methods, the median life expectancy after diagnosis is only 15 months. This extreme treatment resistance is primarily due to changes in the tumor microenvironment (TME). Glioblastomas sometimes recruit normal cells to aid growth, and neural progenitor cells (NPCs) have been observed migrating toward glioblastomas. Understanding the interaction between tumor and non-tumor cells in the TME is critical to developing new treatments. Recently, researchers examined the effects of extracellular vesicles (EVs) from glioblastoma cell lines on the cell lines themselves and mouse NPCs (mNPCs). In both glioblastoma cell lines and mNPCs, glioblastoma-derived EVs promoted proliferation and migration. Using a combination of proteomic profiling and laboratory assays, researchers examined the potential mechanisms of this effect and identified the PI3K-Akt-mTOR pathway as a key mediator..."

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:

"Gastric cancer is one of the highest mortality cancer types, and the leading cause of gastric cancer is persistent Helicobacter pylori infection. H. pylori secretes the enzyme HtrA, which cleaves adhesion proteins like E-cadherin and allows H. pylori to cross the epithelium. Recently, researchers used proteomics to find novel targets of HtrA associated with H. pylori. They confirmed E-cadherin as a target and identified human desmoglein-2 (hDsg2), neuropilin-1, ephrin-B2, and semaphorin-4D as potential targets. hDsg2 is a component of the desmosome junctions, which play important roles in epithelial cell-to-cell adhesion. Given the importance of cell-to-cell adhesion to epithelial health, the researchers focused on hDsg2. In vitro tests confirmed that HtrA secreted by H. pylori, and not other host cell proteases, cleaved hDsg2. This study is the first to demonstrate that HtrA secreted by H. pylori directly breaks down hDsg2 and suggests that HtrA is a ‘master key’ that allows H..."

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:

"Salt marshes are highly productive intertidal ecosystems. Among the most effective carbon sequestering ecosystems per unit area, they can generate abundant organic carbon, which is produced in the form of lignocellulose, a renewable and sustainable feedstock for fuel production. Once lignocellulose is generated, it is then metabolized by communities of functionally diverse microbes. Unfortunately, the organisms and precise mechanisms regulating this process remain unknown due to the complex and underexplored environment. A new study sought to better understand lignocellulose decomposition. Using proteomics and sequencing, they evaluated the microbes residing in a natural established UK salt marsh. They found that the community was dominated by Gammaproteobacteria, Bacteroidetes, and Deltaproteobacteria. 42 families of lignocellulolytic bacteria were identified, which secrete glycoside hydrolase family enzymes to degrade lignocellulose..."

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

This course provides an intensive introduction to artificial intelligence and its applications to problems of medical diagnosis, therapy selection, and monitoring and learning from databases. It meets with lectures and recitations of 6.034 Artificial Intelligence, whose material is supplemented by additional medical-specific readings in a weekly discussion session. Students are responsible for completing all homework assignments in 6.034 and for additional problems and/or papers.

TED Studies, created in collaboration with Wiley, are curated video collections — supplemented by rich educational materials — for students, educators and self-guided learners. The speakers in Rethinking Cancer give the talk of their lives about the prevention, detection and treatment of one of the leading causes of death worldwide: cancer. In this course, you’ll question fundamental concepts about what cancer is and rethink how cancer research should be conducted.

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:

"In Wolfram syndrome (WFS), intracellular endoplasmic reticulum stress and reduced levels of the protein wolframin lead to diabetes and neurodegeneration. In addition, deficiency of the wolframin-encoding gene, WFS1, is known to disrupt calcium balance and change mitochondrial dynamics. Unfortunately, there is no effective treatment for WFS, but better characterization of its mechanisms might aid in therapy development. To further investigate WFS, a recent study analyzed the mRNA transcript and protein profiles in a human cell WFS model. The levels of proteins in various signaling pathways differed between the WFS cells and normal control cells. For example, proteins involved in oxidative phosphorylation, the major energy-producing pathway in mitochondria, were downregulated in the WFS cells. while proteins in other energy generation pathways were upregulated..."

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

Small molecules are chemicals that can interact with proteins to affect their functions. Learn about the structure and biological functions of various small molecules like sugar and caffeine. Also featured on the HHMI DVD, Scanning Life's Matrix: Genes, Proteins, and Small Molecules. Available free from HHMI.