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:

"Microbial metagenomes are like a blueprint of all the functions performed by a microbial community. Some microbes can't be grown in the lab, so metagenomics is important for investigating otherwise-unknown microbial "dark matter". Short-read sequencing provides large amounts of data, but it's hard to assemble into complete genomes. A recent study combined short-read data with nanopore long-read data using Iterative Hybrid Assembly (IHA). The researchers reconstructed 49 metagenome-assembled genomes (MAGs), including some with very low coverage. In total, 34 MAGs did not belong to any known genus, representing unknown microbe groups. The IHA method revealed more of the genes present than a short-read-only approach and showed that the anammox genome of genus Ca. Brocadia contains two identical hydrazine synthase genes. The current method is best for enriched microbial communities and will be extended to high-complexity samples in the future..."

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:

"The ribosomal RNA (rRNA) gene approach to sequencing genetic material has revolutionized microbiome science. But it isn’t perfect. The method relies on the assumption that counts of rRNA genes translate into microbial abundance. Exceptions to that rule, however, are known, such as the observation that rRNA gene counts can be higher in fast-growing microbes. Now, researchers report a new relationship between rRNA genes and cell volume that could help correct for biases inherent to microbiome studies. An analysis of previously reported data showed that the number of 16S or 18S RNA genes per cell follows an allometric power law of cell volume. Applying this relationship to a dataset for bacteria found in intertidal rocks allowed for more accurate biovolume and cell count distributions to be estimated for all taxa detected. The development of more comprehensive cell-size databases could help strengthen the bias-correcting relationship and boost the power of current microbiome analyses..."

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

This course reviews the key genomic technologies and computational approaches that are driving advances in prognostics, diagnostics, and treatment. Throughout the semester, emphasis will return to issues surrounding the context of genomics in medicine including: what does a physician need to know? what sorts of questions will s/he likely encounter from patients? how should s/he respond? Lecturers will guide the student through real world patient-doctor interactions. Outcome considerations and socioeconomic implications of personalized medicine are also discussed. The first part of the course introduces key basic concepts of molecular biology, computational biology, and genomics. Continuing in the informatics applications portion of the course, lecturers begin each lecture block with a scenario, in order to set the stage and engage the student by showing: why is this important to know? how will the information presented be brought to bear on medical practice? The final section presents the ethical, legal, and social issues surrounding genomic medicine. A vision of how genomic medicine relates to preventative care and public health is presented in a discussion forum with the students where the following questions are explored: what is your level of preparedness now? what challenges must be met by the healthcare industry to get to where it needs to be?

Lecturers
Dr. Atul J. Butte
Dr. Steven A. Greenberg
Dr. Alvin Thong-Juak Kho
Dr. Peter Park
Dr. Marco F. Ramoni
Dr. Alberto A. Riva
Dr. Zoltan Szallasi
Dr. Jeffrey Mark Drazen
Dr. Todd Golub
Dr. Joel Hirschhorn
Dr. Greg Tucker-Kellogg
Dr. Scott Weiss

The human genome project was one the most important human discoveries in the past 100 years. It creates a map of every gene in the human body.  Through this lesson you will explore the history of the genome project, its applications today, and implications for your life.  In addition, you will reflect on its impact on your life and determine if you think this is a positive or negative change. Based on your understanding, you will look at different perspectives with empathy to better understand how this technology impacts other people's lives.StandardsBIO.B.2.4Explain how genetic engineering has impacted the fields of medicine, forensics, and agriculture (e.g., selective breeding, gene splicing, cloning, genetically modified organisms, gene therapy).

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:

"Advances in genomic laboratory and bioinformatics techniques have allowed us to infer microbial ecology information from genomes. This ability has led to great advances in microbiome science; however, there is not yet a standard comprehensive workflow for functional annotation. Some software tools annotate metabolic functions, but the new tool 'METABOLIC' improves upon this and expands into biogeochemical pathways like the carbon cycle. METABOLIC takes sequence inputs from isolates, metagenome-assembled genomes, or single-cell genomes. The data can be processed through two workflow scales: genome and/or community. The genome-scale workflow annotates the genomes and validates motifs of conserved protein residues. It also analyzes metabolic pathways and calculates the microbial contributions to individual biogeochemical processes and cycles. The community-scale workflow adds to this by first determining the genome abundance in the microbiome..."

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

How will researchers harness the genetic potential of marine organisms? Join Dr. Terry Gaasterland as she describes how scientists at the new Scripps Genome Center are pioneering research in marine genomes. (54 minutes)

This fun Web site is part of OLogy, where kids can collect virtual trading cards and create projects with them. Here, they learn about the human genome project by clicking through an online slide show, hosted by kids, that answers these questions: What's a genome, anyway?What is the human genome project? What does it mean to me?

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:

"Heritable traits such as height or disease vary from person to person. One way to explain these variations is by looking at the genomes of large populations. That’s the aim of genome-wide association studies, or GWASs. Unfortunately, GWASs often come up short – explaining only a small fraction of trait heritability. That has many researchers looking to the human microbiome for this “missing heritability”. But according to a new a perspective piece, there could be a few problems with that approach. While individuals have only one genomic sequence, they’re host to numerous microbiomes that evolve over time. That means that it would likely be incorrect to consider the microbiome as an extension of the human genome. Additionally, microbiomes may be strongly shaped by environmental factors, making them irrelevant to the genetic component of human heritability. Microbiome sequencing data could still have a place in heritability studies..."

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