RNA centric research is of growing importance for medicine and molecular biology. Increasing amounts of data from deep sequencing experiments create a demand for automatic analysis and interpretation solutions.
The RNA-Workbench offers a wide range of tools covering classic RNA-bioinformatics as well as RNA-seq fields. Predefined workflows for the annotation of non-coding RNAs or identification of differentially expressed genes are subsets of over 50 included tools from the categories RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. RNA specific visualisation solutions for dot-bracket plots and secondary structures are part of the workbench.
In contrast to pre-existing solutions, our community driven approach allowes us to include classic RNA-bioinformatics tools often with the direct support of the tool-authors. These contributions enable us to provide excellent documentation, training material and interactive tours demonstrating the functionality of the workbench.
Building on the Galaxy framework the workbench offers sophisticated analyses to users without command line knowledge, while emphasising reproducibility, customization and effortless scale up to larger infrastructures. The workbench is implemented as Galaxy Docker flavour and therefore easily extendable by additional tools, workflows, tours or training data, that can be installed from the Galaxy ToolShed. The workbench will be further improved and maintained in an ongoing community effort.
BioDec, based near Bologna, Italy, provides top-notch services, solutions, and consulting in the field of lab data management and in postgenomics "in silico" research. The presentation summarizes our main achievements and describes our commercial offer.
RNA-Seq Analysis: Everything You Always Wanted to Know...and then somebasepairtech
Computational biologist and Basepair founder, Dr. Amit Sinha (@ausinha) helps viewers navigate the world of RNA-Seq analysis. Topics include: Introduction to RNA-Seq, tools and workflows for analysis, visualization and figures, Q & A. More info at: https://www.basepairtech.com/
AGRF in conjunction with EMBL Australia recently organised a workshop at Monash University Clayton. This workshop was targeted at beginners and biologists who are new to analysing Next-Gen Sequencing data. The workshop also aimed to provide users with a snapshot of bioinformatics and data analysis tips on how to begin to analyse project data. An introduction to RNA-seq data analysis was presented by AGRF Senior Bioinformatician Dr. Sonika Tyagi.
Presented: 1st August 2012
BioDec, based near Bologna, Italy, provides top-notch services, solutions, and consulting in the field of lab data management and in postgenomics "in silico" research. The presentation summarizes our main achievements and describes our commercial offer.
RNA-Seq Analysis: Everything You Always Wanted to Know...and then somebasepairtech
Computational biologist and Basepair founder, Dr. Amit Sinha (@ausinha) helps viewers navigate the world of RNA-Seq analysis. Topics include: Introduction to RNA-Seq, tools and workflows for analysis, visualization and figures, Q & A. More info at: https://www.basepairtech.com/
AGRF in conjunction with EMBL Australia recently organised a workshop at Monash University Clayton. This workshop was targeted at beginners and biologists who are new to analysing Next-Gen Sequencing data. The workshop also aimed to provide users with a snapshot of bioinformatics and data analysis tips on how to begin to analyse project data. An introduction to RNA-seq data analysis was presented by AGRF Senior Bioinformatician Dr. Sonika Tyagi.
Presented: 1st August 2012
ICAR 2015
Workshop 10 (TUESDAY, JULY 7, 2015, 4:30-6:00 PM)
The Arabidopsis information portal for users and developers
Nick Provart (University of Toronto)
A Community Collaborator Perspective: Case study 1 - BioAnalytic Resource
Functional annotation assigns functions to the genomic elements found by structural annotation, by relating them to biological processes such as the cell cycle, cell death, development, metabolism, etc. It may also be used as an additional quality check by identifying elements that may have been annotated by error. These annotations come in two types, parameter annotations and return type annotations. One large benefit is that they can provide much needed explanation to the reader as to what type a function parameter expects or a function returns. In this example, adding a string explanation to two vague parameters.
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsGolden Helix Inc
Analysis of rare variants for population-level data is becoming a more common component of genomic research. Whether using exome chips, whole-exome sequencing, or even whole-genome sequencing, rare variation analysis requires a unique analytic perspective.
In this presentation, we will review some of the tools available in SVS for large sequenced cohorts including summarization, visualization, and statistical analysis of rare variants using KBAC, CMC, and other methods.
Special attention will be given to useful functions available for download from the SVS scripts repository.
The Bioinformatics Core Facility implemented during the years a number of procedures and pipelines for providing high quality results to an increasing number of users. Here we present our experience with migrating some of extensively used pipelines to the Nextflow framework and creating docker/singularity containers for reproducibility.
Enabling Large Scale Sequencing Studies through Science as a ServiceJustin Johnson
Now
“Now” generation sequencing has drastically changed the traditional costs and infrastructure within the sequencing community. There are several technologies, platforms and algorithms that show promise, but it is not always intuitive where to start. This uncertainty is compounded by the fact that commonly used analysis tools are difficult to build, maintain, and run effectively. Sample acquisition and preparation is quickly becoming a bottleneck as projects move from small sample sizes to hundreds or even thousands of samples. We will present case studies highlighting information, methods, challenges and opportunities in leveraging large scale high throughput sequencing and bioinformatics. Specifically we will highlight a recent genome-wide study of methylation patterns in 1575 individuals with Schizophrenia. We will also discuss several cancer transcriptome and exome sequencing projects as well as a human pathogen transcriptome characterization project consisting of multiple organisms and almost a billion reads.
The Future
The Ion Torrent PGM machine is a very promising, rapid throughput, ultra scalable sequencer that could play an integral part in future human health studies. Applications such as microbial whole genome sequencing, metagenomic characterization of environmental and microbiome sample, and targeted resequencing projects stand to benefit from this technology over time. To date we have completed more than 25 runs on a single PGM and will comment on the setup as well as sequence data and analysis.
Ajith Ranabahu, Priti Parikh, Maryam Panahiazar, Amit Sheth and Flora Logan-Klumpler: Kino : Making Semantic Annotations Easier, Presented at 5th Intl Conf on Semantic Computing (ICSC2011), Palo Alto, CA, September 2011.
This talk explores how principles derived from experimental design practice, data and computational models can greatly enhance data quality, data generation, data reporting, data publication and data review.
Under the Hood of Alignment Algorithms for NGS Researchers Golden Helix Inc
Most NGS analysis is founded on a very simple and powerful principle: look only at the differences of your data to a reference genome of your species. Alignment algorithms are the workhorse of this approach and accounts for the vast majority of the compute time necessary in a secondary analysis workflow. In this webcast, Gabe Rudy covers the history of alignment algorithms of short read, high-throughput sequencing data and the set of tools that represent the state of the art.
We will use the newly launched GenomeBrowse 2.0 visualization engine to review examples of different alignment artifacts, false-positive variant calls, and other alignment and variant meta-data.
What you can expect to learn:
- How all alignment algorithms are a trade-off of speed versus accuracy, and what those trade-offs can mean with your data.
- How the human reference sequence causes alignment artifacts, and how you can spot them.
- How BWA, BWA-MEM and BWA-SW differ.
- How local re-alignment works to improve variant calling, and when you will see it and won't see it in action in your data.
- How to read a CIGAR string and other per-alignment data to investigate alignments at a particular locus.
We will use the newly launched GenomeBrowse 2.0 visualization engine to review examples of different alignment artifacts, false-positive variant calls, and other alignment and variant meta-data.
Apollo is a web-based application that supports and enables collaborative genome curation in real time, allowing teams of curators to improve on existing automated gene models through an intuitive interface. Apollo allows researchers to break down large amounts of data into manageable portions to mobilize groups of researchers with shared interests.
The i5K, an initiative to sequence the genomes of 5,000 insect and related arthropod species, is a broad and inclusive effort that seeks to involve scientists from around the world in their genome curation process, and Apollo is serving as the platform to empower this community.
This presentation is an introduction to Apollo for the members of the i5K Pilot Project working on species of the order Hemiptera.
ICAR 2015
Workshop 10 (TUESDAY, JULY 7, 2015, 4:30-6:00 PM)
The Arabidopsis information portal for users and developers
Nick Provart (University of Toronto)
A Community Collaborator Perspective: Case study 1 - BioAnalytic Resource
Functional annotation assigns functions to the genomic elements found by structural annotation, by relating them to biological processes such as the cell cycle, cell death, development, metabolism, etc. It may also be used as an additional quality check by identifying elements that may have been annotated by error. These annotations come in two types, parameter annotations and return type annotations. One large benefit is that they can provide much needed explanation to the reader as to what type a function parameter expects or a function returns. In this example, adding a string explanation to two vague parameters.
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsGolden Helix Inc
Analysis of rare variants for population-level data is becoming a more common component of genomic research. Whether using exome chips, whole-exome sequencing, or even whole-genome sequencing, rare variation analysis requires a unique analytic perspective.
In this presentation, we will review some of the tools available in SVS for large sequenced cohorts including summarization, visualization, and statistical analysis of rare variants using KBAC, CMC, and other methods.
Special attention will be given to useful functions available for download from the SVS scripts repository.
The Bioinformatics Core Facility implemented during the years a number of procedures and pipelines for providing high quality results to an increasing number of users. Here we present our experience with migrating some of extensively used pipelines to the Nextflow framework and creating docker/singularity containers for reproducibility.
Enabling Large Scale Sequencing Studies through Science as a ServiceJustin Johnson
Now
“Now” generation sequencing has drastically changed the traditional costs and infrastructure within the sequencing community. There are several technologies, platforms and algorithms that show promise, but it is not always intuitive where to start. This uncertainty is compounded by the fact that commonly used analysis tools are difficult to build, maintain, and run effectively. Sample acquisition and preparation is quickly becoming a bottleneck as projects move from small sample sizes to hundreds or even thousands of samples. We will present case studies highlighting information, methods, challenges and opportunities in leveraging large scale high throughput sequencing and bioinformatics. Specifically we will highlight a recent genome-wide study of methylation patterns in 1575 individuals with Schizophrenia. We will also discuss several cancer transcriptome and exome sequencing projects as well as a human pathogen transcriptome characterization project consisting of multiple organisms and almost a billion reads.
The Future
The Ion Torrent PGM machine is a very promising, rapid throughput, ultra scalable sequencer that could play an integral part in future human health studies. Applications such as microbial whole genome sequencing, metagenomic characterization of environmental and microbiome sample, and targeted resequencing projects stand to benefit from this technology over time. To date we have completed more than 25 runs on a single PGM and will comment on the setup as well as sequence data and analysis.
Ajith Ranabahu, Priti Parikh, Maryam Panahiazar, Amit Sheth and Flora Logan-Klumpler: Kino : Making Semantic Annotations Easier, Presented at 5th Intl Conf on Semantic Computing (ICSC2011), Palo Alto, CA, September 2011.
This talk explores how principles derived from experimental design practice, data and computational models can greatly enhance data quality, data generation, data reporting, data publication and data review.
Under the Hood of Alignment Algorithms for NGS Researchers Golden Helix Inc
Most NGS analysis is founded on a very simple and powerful principle: look only at the differences of your data to a reference genome of your species. Alignment algorithms are the workhorse of this approach and accounts for the vast majority of the compute time necessary in a secondary analysis workflow. In this webcast, Gabe Rudy covers the history of alignment algorithms of short read, high-throughput sequencing data and the set of tools that represent the state of the art.
We will use the newly launched GenomeBrowse 2.0 visualization engine to review examples of different alignment artifacts, false-positive variant calls, and other alignment and variant meta-data.
What you can expect to learn:
- How all alignment algorithms are a trade-off of speed versus accuracy, and what those trade-offs can mean with your data.
- How the human reference sequence causes alignment artifacts, and how you can spot them.
- How BWA, BWA-MEM and BWA-SW differ.
- How local re-alignment works to improve variant calling, and when you will see it and won't see it in action in your data.
- How to read a CIGAR string and other per-alignment data to investigate alignments at a particular locus.
We will use the newly launched GenomeBrowse 2.0 visualization engine to review examples of different alignment artifacts, false-positive variant calls, and other alignment and variant meta-data.
Apollo is a web-based application that supports and enables collaborative genome curation in real time, allowing teams of curators to improve on existing automated gene models through an intuitive interface. Apollo allows researchers to break down large amounts of data into manageable portions to mobilize groups of researchers with shared interests.
The i5K, an initiative to sequence the genomes of 5,000 insect and related arthropod species, is a broad and inclusive effort that seeks to involve scientists from around the world in their genome curation process, and Apollo is serving as the platform to empower this community.
This presentation is an introduction to Apollo for the members of the i5K Pilot Project working on species of the order Hemiptera.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
1. The RNA Workbench - reproducible,
transparent, and accessible RNA research
Florian Eggenhofer, Bj¨orn Gr¨uning, B´er´enice Batut, J¨org
Fallmann, Andrea Bagnacani, Peter F. Stadler, Rolf Backofen
and the RNA Workbench Team
Lehrstuhl Bioinformatik
University of Freiburg
16.03.2018
2. Goals of the RNA Workbench
Comprehensive set of RNA-bioinformatics tools
3. Goals of the RNA Workbench
Comprehensive set of RNA-bioinformatics tools
Community - authors and users
4. Goals of the RNA Workbench
Comprehensive set of RNA-bioinformatics tools
Community - authors and users
Set of predefined workflows and associated
descriptions/training material
5. Goals of the RNA Workbench
Comprehensive set of RNA-bioinformatics tools
Community - authors and users
Set of predefined workflows and associated
descriptions/training material
Easy and stable dissemination via Galaxy in Docker
11. Workflows
Currently six workflows in the RNA workbench
RNA
HTS analysisncRNA analysis
Structured RNA
RNA family model
C/D box scan
RNA-seq
PARCLIP
AREsite2-CLIP
12. Workflow - Analysis of non-coding RNAs
Test for functional structure via conservation
13. Workflow - Analysis of non-coding RNAs
Test for functional structure via conservation
14. Workflow - Analysis of non-coding RNAs
Test for functional structure via conservation
15. Workflow - Analysis of non-coding RNAs
Test for functional structure via conservation
16. Workflow - Analysis of non-coding RNAs
Test for functional structure via conservation
17. Workflow - Analysis of non-coding RNAs
Test for functional structure via conservation
18. Workflow - RNA family model construction
RNA family model construction
19. Workflow - RNA family model construction
RNA family model construction
20. Workflow - RNA family model construction
RNA family model construction
21. Workflow - RNA family model construction
RNA family model construction
34. Training & Usage
Training
Training sessions (Introduction, HTS data and RNA-seq
analyses)
http://training.galaxyproject.org
Galaxy Interactive Tours
35. Training & Usage
Training
Training sessions (Introduction, HTS data and RNA-seq
analyses)
http://training.galaxyproject.org
Galaxy Interactive Tours
Using the workbench
36. Training & Usage
Training
Training sessions (Introduction, HTS data and RNA-seq
analyses)
http://training.galaxyproject.org
Galaxy Interactive Tours
Using the workbench
docker run galaxy-rna-workbench
37. Training & Usage
Training
Training sessions (Introduction, HTS data and RNA-seq
analyses)
http://training.galaxyproject.org
Galaxy Interactive Tours
Using the workbench
docker run galaxy-rna-workbench
OSX and Windows using the graphical tool Kitematic
