The document summarizes the Bacterial Bioinformatics Resource Center (BRC), which merges several bioinformatics resources to support infectious disease research. The BRC contains over 130,000 microbial genomes with uniform annotations across genes, proteins, pathways, and more. It also includes curated data on antimicrobial resistance for over 15,000 genomes. The BRC enables users to analyze genomes, perform comparative analyses, and has deployed machine learning to predict antimicrobial resistance phenotypes from genomic data.
The presentation was done as part of the course STAT 504 titled Quantitative Genetics in Second Semester of MSc. Agricultural Statistics at Agricultural College, Bapatla under ANGRAU, Andhra Pradesh
Dr. S. MANIKANDAN, M.Sc., Ph.D
Lecturer in Botany
Thiruvalluvar University Model Constituent College,
Tittagudi 606 106, Tamil Nadu, India.
Email id: drgsmanikandan@gmail.com
To handle complex Traits like Yield, different stress we must do modification in DNA molecular breeding techniques help us to do such changes in DNA to archive the Goals.
Marker assisted whole genome selection in crop improvementSenthil Natesan
Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground selection) and accelerating the recovery of the recurrent parent genome (background selection). MAS has been more widely employed for simply inherited traits than for polygenic traits, although there are a few success stories in improving quantitative traits through MAS
The presentation was done as part of the course STAT 504 titled Quantitative Genetics in Second Semester of MSc. Agricultural Statistics at Agricultural College, Bapatla under ANGRAU, Andhra Pradesh
Dr. S. MANIKANDAN, M.Sc., Ph.D
Lecturer in Botany
Thiruvalluvar University Model Constituent College,
Tittagudi 606 106, Tamil Nadu, India.
Email id: drgsmanikandan@gmail.com
To handle complex Traits like Yield, different stress we must do modification in DNA molecular breeding techniques help us to do such changes in DNA to archive the Goals.
Marker assisted whole genome selection in crop improvementSenthil Natesan
Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground selection) and accelerating the recovery of the recurrent parent genome (background selection). MAS has been more widely employed for simply inherited traits than for polygenic traits, although there are a few success stories in improving quantitative traits through MAS
Molecular Breeding in Plants is an introduction to the fundamental techniques...UNIVERSITI MALAYSIA SABAH
This slide describe the process of molecular breeding in plants which involves the application of molecular markers for Marker Assisted Selection and Marker Assisted Breeding.
A genetic marker is a gene or DNA sequence with a known location on a chromosome that can be used to identify individuals or species. It can be described as a variation (which may arise due to mutation or alteration in the genomic loci) that can be observed. A genetic marker may be a short DNA sequence, such as a sequence surrounding a single base-pair change (single nucleotide polymorphism, SNP), or a long one, like minisatellites.
Molecular Marker and It's ApplicationsSuresh Antre
Molecular (DNA) markers are segments of DNA that can be detected through specific laboratory techniques. With the advent of marker-assisted selection (MAS), a new breeding tool is now available to make more accurate and useful selections in breeding populations.
Definition, principle, Chemical used during the process, application, advantages, and disadvantages of both techniques. along with relevant case study for better understand
Marker Assisted Selection in Crop BreedingPawan Chauhan
Marker Assisted Selection is a value addition to conventional methods of Crop Breeding. It has been gaining importance in plant breeding with new generation of plant breeders and to get accurate and fast desired result from plant breeding.
Vector mediated gene transfer methods for transgenesis in Plants.Akshay More
Presentation include Vector mediated gene transfer methods for trans-genesis in Plants. Only Vector-based methods are covered. Vectors includes Bacteria, Viruses, transposable genetic elements. Other possible vectors for transgenesis are also covered.
Quantifying the content of biomedical semantic resources as a core for drug d...Syed Muhammad Ali Hasnain
The biomedical research community is providing large-scale data sources to enable knowledge discovery from the data alone, or from novel scientific experiments in combination with the existing knowledge.
Increasingly semantic Web technologies are being developed and used including ontologies, triple stores and combinations thereof.
The amount of data is constantly increasing as well as the complexity of data.
Since the data sources are publicly available, the amount of content can be derived giving an overview on the accessible content but also on the state of the data representation in comparison to the existing content.
For a better understanding of the existing data resources, i.e.\ judgments on the distribution of data triples across concepts, data types and primary providers, we have performed a comprehensive analysis which delivers an overview on the accessible content for semantic Web solutions.
It can be derived that the information related to genes, proteins and chemical entities form the center, whereas the content related to diseases and pathways forms a smaller portion.
Further data relates to dietary content and specific questions such as cancer prevention and toxicological effects of drugs.
Molecular Breeding in Plants is an introduction to the fundamental techniques...UNIVERSITI MALAYSIA SABAH
This slide describe the process of molecular breeding in plants which involves the application of molecular markers for Marker Assisted Selection and Marker Assisted Breeding.
A genetic marker is a gene or DNA sequence with a known location on a chromosome that can be used to identify individuals or species. It can be described as a variation (which may arise due to mutation or alteration in the genomic loci) that can be observed. A genetic marker may be a short DNA sequence, such as a sequence surrounding a single base-pair change (single nucleotide polymorphism, SNP), or a long one, like minisatellites.
Molecular Marker and It's ApplicationsSuresh Antre
Molecular (DNA) markers are segments of DNA that can be detected through specific laboratory techniques. With the advent of marker-assisted selection (MAS), a new breeding tool is now available to make more accurate and useful selections in breeding populations.
Definition, principle, Chemical used during the process, application, advantages, and disadvantages of both techniques. along with relevant case study for better understand
Marker Assisted Selection in Crop BreedingPawan Chauhan
Marker Assisted Selection is a value addition to conventional methods of Crop Breeding. It has been gaining importance in plant breeding with new generation of plant breeders and to get accurate and fast desired result from plant breeding.
Vector mediated gene transfer methods for transgenesis in Plants.Akshay More
Presentation include Vector mediated gene transfer methods for trans-genesis in Plants. Only Vector-based methods are covered. Vectors includes Bacteria, Viruses, transposable genetic elements. Other possible vectors for transgenesis are also covered.
Quantifying the content of biomedical semantic resources as a core for drug d...Syed Muhammad Ali Hasnain
The biomedical research community is providing large-scale data sources to enable knowledge discovery from the data alone, or from novel scientific experiments in combination with the existing knowledge.
Increasingly semantic Web technologies are being developed and used including ontologies, triple stores and combinations thereof.
The amount of data is constantly increasing as well as the complexity of data.
Since the data sources are publicly available, the amount of content can be derived giving an overview on the accessible content but also on the state of the data representation in comparison to the existing content.
For a better understanding of the existing data resources, i.e.\ judgments on the distribution of data triples across concepts, data types and primary providers, we have performed a comprehensive analysis which delivers an overview on the accessible content for semantic Web solutions.
It can be derived that the information related to genes, proteins and chemical entities form the center, whereas the content related to diseases and pathways forms a smaller portion.
Further data relates to dietary content and specific questions such as cancer prevention and toxicological effects of drugs.
Next Generation Sequencing for Identification and Subtyping of Foodborne Pat...Nathan Olson
"Next Generation Sequencing for Identification and Subtyping of Foodborne Pathogens" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by the National Institute for Standards and Technology October 2014 by Rebecca Lindsey, PhD from Enteric Diseases Laboratory Branch of the CDC.
Genomic aided selection for crop improvementtanvic2
In last Several years novel genetic and genomics approaches are expended. Genetics and genomics have greatly enhanced our understanding of the structural and functional aspects of plant genomes.
In the late Fall and Winter of 2018, the Pistoia Alliance in cooperation with Elsevier and charitable organizations Cures within Reach and Mission: Cure ran a datathon aiming to find drugs suitable for treatment of childhood chronic pancreatitis, a rare disease that causes extreme suffering. The datathon resulted in identification of four candidate compounds in a short time frame of just under three months. In this webinar our speakers discuss the technologies that made this leap possible
Next Generation Sequencing for Identification and Subtyping of Foodborne Pat...nist-spin
"Next Generation Sequencing for Identification and Subtyping of Foodborne Pathogens" presentation at the Standards for Pathogen Identification via NGS (SPIN) workshop hosted by National Institute for Standards and Technology October 2014 by Rebecca Lindsey, PhD from Enteric Diseases Laboratory Branch of the CDC.
From Sequence to Knowledge (Tools for Phage Genome Annotation)Ramy K. Aziz
This is an introduction to the PATRIC Phage Genomics Workshop at the 24th Biennial Evergreen International Phage Meeting, Aug 6 2021.
It introduces the workshop outline, system, and the genome annotation workflow
The Opera of Phantome - 2017 (presented at the 22nd Biennial Evergreen Phage ...Ramy K. Aziz
Tools and Methods developed under the SEED/RAST/PhAnToMe (http://www.phantome.org) project and sequels adopted in RASTtk and PATRIC. The tools and database rely on the Subsystems Technology, the SEED (http://theseed.org) environment, and RAST server (http://rast.nmpdr.org).
This is a part of the Phage Genomics Workshop at the 22nd Biennial Evergreen International Phage Meeting, Aug 6 2017.
From Sequence to Knowledge (Phage Genomics Workshop Intro at the 22nd Biennia...Ramy K. Aziz
This is an introduction to the Phage Genomics Workshop at the 22nd Biennial Evergreen International Phage Meeting, Aug 6 2017.
It introduces the workshop outline, system, and the genome annotation workflow
From Sequence to Knowledge: The Art and Science of Phage Genome AnnotationRamy K. Aziz
First part of the phage annotation workshop at the 2016 EMBO Viruses of Microbes Meeting (Liverpool, UK), presented on 21 July 2016 (http://events.embo.org/16-virus-microbe)
The Opera of Phantome - 2016 (presented at the EMBO Viruses of Microbes 2016 ...Ramy K. Aziz
Tools and Methods developed under the PhAnToMe (http://www.phantome.org) project between 2009-2012—and updated in 2015. The tools and database rely on the Subsystems Technology, the SEED (http://theseed.org) environment, and RAST server (http://rast.nmpdr.org)
This is the fifth such presentation; this year at the EMBO Viruses of Microbes 2016 Meeting, 21 July 2016 (http://events.embo.org/16-virus-microbe)
Systems Biology and Genomics of Microbial PathogensRamy K. Aziz
Talk at SCITA-BIOFANS (02 Feb 2016), entitled
"Systems Biology and Genomics of Microbial Pathogens:
From virulence gene discovery to vaccine development and therapeutic intervention"
The Opera of Phantome - Version 2.0 (presented at the 21st Biennial Evergreen...Ramy K. Aziz
Tools and Methods developed under the PhAnToMe (http://www.phantome.org) project between 2009-2012—and updated in 2015. The tools and database rely on the Subsystems Technology, the SEED (http://theseed.org) environment, and RAST server (http://rast.nmpdr.org)
This is the fourth presentation at the Phage Genomics Workshop at the 21st Biennial Evergreen International Phage Meeting, Aug 2 2015.
What doesn't kill you makes you stronger!
A presentation on the constructive ways for giving and receiving feedback—adapted from: "Developing Leadership Skills", by Alfred Darmanin
The central dogma of molecular biology, systems biology, and -omics from football's (aka soccer) perspective...
The #badomics title is dedicated to @phylogenomics (aka Jonathan Eisen)
"The Opera of PhAnToMe": Phage Annotation Tools at the 20th Biennial Evergree...Ramy K. Aziz
Tools and Methods developed under the PhAnToMe (http://www.phantome.org) project between 2009-2012 using the Subsystems Technology, the SEED (http://theseed.org) environment, and RAST server (http://rast.nmpdr.org)
Third presentation at the Phage Genomics Workshop at the 20th Biennial Evergreen International Phage Meeting
Introduction to PhAnToMe Workshop, 19th Evergreen Phage Meeting, 2011Ramy K. Aziz
An introduction to a tutorial on using the PhAnToMe (Phage Annotation Tools and Methods) website, databases (Phage SEED, Phage Metadata), and programs: phiRAST, PhageBioBIKE, and phiSIGNs
Talk by Ramy K. Aziz in the second TWAS/BioVisionAlexandria.NXT in Alexandria- Egypt (10-11 April 2010) about "Open Acess and The Next Revolution in Scholarly Publishing".
The slides are also contributed by Mark Patterson, Björn Brembs, and Peter Binfield.
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.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
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.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
4. NIAID-funded Bacterial Bioinformatics Resource Center (BRC)
designed to support infectious disease research
Special emphasis on 22 pathogenic genera
◦ Bacillus, Bartonella, Borrelia, Brucella, Burkholderia, Campylobacter,
Chlamydophila, Clostridium, Coxiella, Ehrlichia, Escherichia, Francisella,
Helicobacter, Listeria, Mycobacterium, Rickettsia, Salmonella, Shigella,
Staphylococcus, Streptococcus, Vibrio, and Yersinia
Merger of PATRIC, RAST, SEED and other resources built by
teams at ANL, UC, FIG, and Virginia Tech
Usage:
◦ >30,000 users
◦ >4,000 citations
5. > 130,000 public microbial genomes – more added every month
◦ 10 host genomes and their annotations
Uniform genome annotations across all genomes
◦ Genes, RNAs, proteins, protein functions, GO, EC, protein families
◦ AMR genes, virulence factors, drug targets, essential genes
◦ Biochemical pathways and metabolic models
◦ Annotations of all public genomes updated every 3-4 months
Curated genome metadata and AMR phenotypes
◦ Disease, isolation, phenotype, clinical and environmental
◦ AMR phenotype data: >15,000 genomes and >100 antibiotics
Transcriptomics data (>800 datasets)
Protein-protein and host-pathogen interactions
Proteomics, metabolomics and Tn-seq data
7. Using curated AMR phenotype data in PATRIC as
training sets, build machine learning classifiers
Predict the antimicrobial resistance (AMR)
phenotypes for new genomes
Predict the genomic regions associated with AMR
Use these predictions to identify new AMR genes
and enhance our understanding of AMR
mechanisms
To date, 40 AMR phenotype prediction classifiers
have been deployed.
8. Genome Assembly
◦ Many Assemblers (short, long reads), Compare Assembly Output
Genome Annotation
◦ High-speed genome annotation using RASTtk and controlled vocabulary from
SEED project
◦ Specialized annotation modules - New
Prediction of AMR phenotype and AMR genes
Prediction of gene essentiality
Similar Genome Finder - New
◦ Find genomes that are most similar to a genome of interest
Proteome Comparison
◦ Compare up to 8 genomes to a reference using bi-directional BLAST hits
Variation Analysis - New
◦ Identify SNPs, SNVs, and insertion / deletion
9. Comparative Analysis and Visualizations
◦ Protein family and metabolic pathway comparisons
◦ Gene list, gene set, projections, heatmaps
◦ Transcriptome analysis, up/down fold changes
◦ Metadata, disease, and PPI data
Comprehensive Searching
◦ AMR genes (ARDB, CARD PATRIC AMR db), genome features,
external ID mapping, similarity, gene pages, gene collections,
correlated genes, genome finder, transcriptome, EC, GO, etc.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31. • Comparison of thousands of protein families across hundreds of genomes
32. • Comparison of thousands of protein families across hundreds of genomes
33. • Comparison of thousands of protein families across hundreds of genomes
34. • Comparison of metabolic pathways across hundreds of genomes
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46. Seeking NIAID funding – funding extension
A possible pre-Evergreen 2019 workshop
Pushing for community annotation
◦ Undergraduate students (I have about 20 in
training)
PLEASE MAKE YOUR VOICE HEARD: What’s
on your wish list?
◦ What do we need to improve phage therapy
resources, in particular?
47. Robert A. Edwards, PhD
RASTtk and PhiRAST development:
Ross Overbeek, Robert Olson, Jim Davis, Gordon
Pusch, Terry Disz, Bruce Parrello
Phage annotators (Phantomers):
Bhakti Dwivedi, Mya Breitbart, et al.
FIG and all SEED annotators:
VeronikaV, SvetaG, OlgaV/Z, et al.
$$
&
NSF
Katelyn McNair
48. SEED, RAST, myRAST, phiRAST:
◦ RAST: Aziz et al., BMC Genomics 2008
◦ SEED servers: Aziz RK,, et al. (2012) PLoS ONE 7(10):
e48053.
◦ Nucleic Acids Res. 2014 Jan;42(Database issue):D206-14
PATRIC: Antonopolus et al., Brief. Bioinf. 2017 Jul
31; Online early
Editor's Notes
AMR Phenotype Prediction in
New Circular Genome Viewer:
Implemented using JavaScript and SVG for better user interaction
Custom tracks for showing select features based on keyword match
Upload user data files and show as new tracks
Useful for showing experimentally verified features, wig files from RNA-seq / ChiP-seq / Tn-seq experiments, binding sites, etc.
New Circular Genome Viewer:
Implemented using JavaScript and SVG for better user interaction
Custom tracks for showing select features based on keyword match
Upload user data files and show as new tracks
Useful for showing experimentally verified features, wig files from RNA-seq / ChiP-seq / Tn-seq experiments, binding sites, etc.
New Compare Region Viewer:
One of the most popular visualization tools in SEED / RAST
Allows you to compare the neighborhood of a gene across multiple genomes
Verify an existing gene function or predict a new one from by inspecting the conserved functions of neighboring genes
Allows one to restrict the scope
to reference / representative genomes for broader cross-taxon comparisons
Or to all public genomes to compare most similar genomes from the same taxon group
Available from the website under Help Menu.
Provide step-by-step instructions on how to use various analysis services and tools at PATRIC.