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The Anna Karenina principle and gum disease
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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:

"“All happy families look alike; each unhappy family is unhappy in its own way” – Leo Tolstoy, Anna Karenina. According to Tolstoy, a healthy home is the result of many factors falling into harmonious order, whereas disharmony is what happens when even one of these factors is out of place. A new study confirms the same principle holds true for the communities of microbes that determine oral health. Researchers mapped microbial DNA from healthy individuals and individuals with one of three forms of gum infection: chronic periodontitis, localized aggressive periodontitis, or generalized aggressive periodontitis. While it’s known that all three forms of periodontitis are microbially derived, the microbial makeup that gives rise to each remains unclear. High-throughput whole genome sequencing revealed that, like Tolstoy's unhappy homes, no two individuals with disease were alike..."

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

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/14/2021
Best-practice evaluation and guidance for human metagenomic studies
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CC BY
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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:

"Metagenomic analysis frequently plays an important role in development pipelines for human fecal microbiome-related products, but validation and standardization of the methods used to extract DNA and assemble sequence libraries for these studies is currently lacking. To close this gap, researchers recently characterized existing protocols for accuracy and precision. First, they tested the quantification accuracy by using a defined mock community of bacteria. Then, the protocols that performed as expected were evaluated for both within- and inter-laboratory precision metrics. The protocols were also tested against the MOSAIC Standards Challenge samples. Lastly, they defined performance metrics for the recommended protocols to provide best-practice guidance. The uptake of the recommendations generated here should improve reproducibility in human metagenomic research and therefore facilitate development and commercialization of human microbiome-related products..."

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

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/14/2021
Biology
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CC BY
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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.

Subject:
Biology
Life Science
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
Date Added:
08/22/2012
Biology, Preface to Biology, Preface to Biology
Conditional Remix & Share Permitted
CC BY-NC
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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.

Subject:
Applied Science
Material Type:
Module
Date Added:
07/10/2017
Charting the complexity of the activated sludge microbiome with a hybrid sequencing strategy
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CC BY
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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 development of long-read sequencing has allowed for the generation of more complete and contiguous genomes in metagenomics studies. However, long-reads are more prone to sequencing errors than short-reads, and these errors can end up incorporated in the draft genomes. Combining short- and long-reads can overcome such errors, but is computationally taxing. To avoid this, researchers developed the ‘Hierarchical Clustering Based Hybrid Assembly (HCBHA) approach.’ This approach first groups the long- and short-reads into candidate bacterial haplotypes and then assembles each group separately, which reduces the computational demand . Researchers tested this framework on a microbiome from activated sludge, an important part of wastewater treatment. The highly complex microbiomes found in activated sludge remove pollutants from wastewater..."

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

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
01/11/2022
Combining single-cell genomics and metagenomics to improve assembly in complex microbial communities
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CC BY
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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:

"High-quality reference genomes are needed to understand the physiology and function of uncultured microbes in complex ecosystems. Metagenomics has been an incredibly useful tool for studying microbial communities, but assigning sequence assemblies accurately to genomes is difficult in microbial species or strains that lack a reference genome. These 'consensus genomes' have lower resolution than those generated from cultured isolates. Combining single-cell genomics with metagenomics may allow us to overcome these methodological weaknesses. Thus, researchers recently developed a framework called SMAGLinker, which integrates single-cell genomes from microfluidic droplets and uses them as guides for metagenome assembly. Compared to metagenomics alone, SMAGLinker showed more precise contig binning and higher recovery rates of rRNA and plasmids in a mock microbial community. In human gut and skin microbiota samples, SMAGLinker returned more genomes than the conventional metagenomics frameworks..."

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

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/13/2021
Community Genomes: using the example of Bauhinia Genome for genomics education. What is a genome project, and why are they important?
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CC BY
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This genomics education lesson plan was formulated and tested on some year 6 students with the help of their teacher Michelle Pardini at the Hong Kong ICS School. Using the example of the ongoing citizen science Bahinia Genome project from Hong Kong it hopes to serve as a model to inspire and inform other national genome projects, and aid the development of crucial genomic literacy and skills across the globe. Inspiring and training a new generation of scientists to use these tools to tackle the biggest threats to mankind: climate change, disease, and food security. It is released under a CC-BY SA 4.0 license, and utilised the following slide deck and final quiz. Promoting open science, all of the data and resources produced from the project is immediately put into the public domain. Please feel free to utilise, adapt and build upon any of these as you wish. The open licence makes these open education resources usable just with attribution and posting of modified resources under a similar manner. Contact BauhiniaGenome if you have any questions or feedback.Bauhinia Genome overviewFor a slidedeck for the lesson plan laid out here you can use the set in slideshare here.

Subject:
Biology
Computer Science
Genetics
Life Science
Material Type:
Lesson Plan
Author:
Scott Edmunds
Michelle Pardini
Rob Davidson
Date Added:
05/12/2016
Data Carpentry R for Genomics
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CC BY
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Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working more effectively with data. The lessons below were designed for those interested in working with Genomics data in R.

Subject:
Applied Science
Computer Science
Material Type:
Lesson
Provider:
NumFocus
Provider Set:
Data Carpentry Genomics Materials
Author:
Kate Hertweck
Ryan Williams
Susan McClatchey
Tracy Teal
Date Added:
03/28/2017
Data Wrangling and Processing for Genomics
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CC BY
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Data Carpentry lesson to learn how to use command-line tools to perform quality control, align reads to a reference genome, and identify and visualize between-sample variation. A lot of genomics analysis is done using command-line tools for three reasons: 1) you will often be working with a large number of files, and working through the command-line rather than through a graphical user interface (GUI) allows you to automate repetitive tasks, 2) you will often need more compute power than is available on your personal computer, and connecting to and interacting with remote computers requires a command-line interface, and 3) you will often need to customize your analyses, and command-line tools often enable more customization than the corresponding GUI tools (if in fact a GUI tool even exists). In a previous lesson, you learned how to use the bash shell to interact with your computer through a command line interface. In this lesson, you will be applying this new knowledge to carry out a common genomics workflow - identifying variants among sequencing samples taken from multiple individuals within a population. We will be starting with a set of sequenced reads (.fastq files), performing some quality control steps, aligning those reads to a reference genome, and ending by identifying and visualizing variations among these samples. As you progress through this lesson, keep in mind that, even if you aren’t going to be doing this same workflow in your research, you will be learning some very important lessons about using command-line bioinformatic tools. What you learn here will enable you to use a variety of bioinformatic tools with confidence and greatly enhance your research efficiency and productivity.

Subject:
Applied Science
Computer Science
Genetics
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Adam Thomas
Ahmed R. Hasan
Aniello Infante
Anita Schürch
Dev Paudel
Erin Alison Becker
Fotis Psomopoulos
François Michonneau
Gaius Augustus
Gregg TeHennepe
Jason Williams
Jessica Elizabeth Mizzi
Karen Cranston
Kari L Jordan
Kate Crosby
Kevin Weitemier
Lex Nederbragt
Luis Avila
Peter R. Hoyt
Rayna Michelle Harris
Ryan Peek
Sheldon John McKay
Sheldon McKay
Taylor Reiter
Tessa Pierce
Toby Hodges
Tracy Teal
Vasilis Lenis
Winni Kretzschmar
dbmarchant
Date Added:
08/07/2020
Disruptor taxa, oral microbes, and strict anaerobes in the human small-intestine microbiome
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CC BY
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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:

"Past research has already tied our gut microbiome to many diseases. However, most research to date has focused on the large intestine, as collecting stool samples is less invasive than sampling the small intestine. Recently, researchers used standard-of-care endoscopies as an opportunity to collect samples from the first section of the small intestine, the duodenum. Using quantitative sequencing, they evaluated the patients' microbial loads. They found preliminary evidence of microbes traveling from the mouth to the small intestine, as 89% of the microbial taxa found in duodenum samples were also present in saliva samples from the same patient. Within the duodenum, the researchers identified a collection of bacterial taxa that, when present, often dominated the microbial population. These ‘disruptor taxa’ appeared to replace the strict anaerobes common in the duodenum and were more prevalent in individuals with the serious GI disorder small intestinal bacterial overgrowth (SIBO)..."

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

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
03/01/2022
Empirical Study of Data Sharing by Authors Publishing in PLoS Journals
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Background Many journals now require authors share their data with other investigators, either by depositing the data in a public repository or making it freely available upon request. These policies are explicit, but remain largely untested. We sought to determine how well authors comply with such policies by requesting data from authors who had published in one of two journals with clear data sharing policies. Methods and Findings We requested data from ten investigators who had published in either PLoS Medicine or PLoS Clinical Trials. All responses were carefully documented. In the event that we were refused data, we reminded authors of the journal's data sharing guidelines. If we did not receive a response to our initial request, a second request was made. Following the ten requests for raw data, three investigators did not respond, four authors responded and refused to share their data, two email addresses were no longer valid, and one author requested further details. A reminder of PLoS's explicit requirement that authors share data did not change the reply from the four authors who initially refused. Only one author sent an original data set. Conclusions We received only one of ten raw data sets requested. This suggests that journal policies requiring data sharing do not lead to authors making their data sets available to independent investigators.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Reading
Provider:
PLOS ONE
Author:
Andrew J. Vickers
Caroline J. Savage
Date Added:
08/07/2020
Estimating disease risk using the microbiome: the Microbial Risk Score
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CC BY
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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:

"Our microbiome has profound impacts on our health, and technological advances have allowed for ever-growing pools of data from microbiome-wide studies. This means that our microbiome could be used to estimate disease risk, but the nature of the data makes the endeavor difficult. Similar issues with using genetics to predict disease risk led to the development of the polygenic risk score. Motivated by the success of that framework, a team of researchers recently developed the microbial risk score (MRS). MRS summarizes the complex microbial profile by first identifying a sub- community consisting of disease-associated microbial taxa and then integrating those microbial taxa into a continuous score based on the alpha diversity of the identified sub-community. MRS can be easily integrated with the other risk scores built upon metatranscriptomics, host genetics, or host transcriptomics, making it useful for 'multi-omics' approaches as well..."

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

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
04/14/2023
Evolution: What Makes us Human?
Only Sharing Permitted
CC BY-NC-ND
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TED Studies, created in collaboration with Wiley, are curated video collections — supplemented by rich educational materials — for students, educators and self-guided learners. in What Makes Us Human?, TED speakers tackle humanity’s oldest and deepest questions by playing with primates, excavating ancient remains, and DNA-mapping family trees. Explore how the next chapters of our own evolutionary story will be written thanks to new technologies that trace our origin. 

Subject:
Life Science
Material Type:
Lecture
Reading
Teaching/Learning Strategy
Provider:
TED
Provider Set:
TED Studies
Author:
James Calcagno
Date Added:
01/06/2017