The document discusses several key databases for nucleotide and protein sequences. It describes NCBI, EMBL, DDBJ, PIR, and SWISS-PROT as the primary databases that store nucleotide and protein sequence data. NCBI, EMBL, and DDBJ work together through the International Nucleotide Sequence Database Collaboration to share data daily and provide a comprehensive set of sequence information. The document provides details on the history and role of each database.
INTRODUCTION.
NCBI.
EMBL.
DDBJ.
CONCLUSION.
REFERENSE.
The National Center for Biotechnology Information (NCBI) is part of the United States National Library of Medicine (NLM), a branch of the National Institutes of Health.
The NCBI is located in Bethesda, Maryland and was founded in 1988 through legislation sponsored by Senator Claude Pepper.
The NCBI houses a series of databases relevant to biotechnology and biomedicine. Major databases include GenBank for DNA sequences and PubMed, a bibliographic database for the biomedical literature.
All these databases are available online through the Entrez search engine.
INTRODUCTION.
NCBI.
EMBL.
DDBJ.
CONCLUSION.
REFERENSE.
The National Center for Biotechnology Information (NCBI) is part of the United States National Library of Medicine (NLM), a branch of the National Institutes of Health.
The NCBI is located in Bethesda, Maryland and was founded in 1988 through legislation sponsored by Senator Claude Pepper.
The NCBI houses a series of databases relevant to biotechnology and biomedicine. Major databases include GenBank for DNA sequences and PubMed, a bibliographic database for the biomedical literature.
All these databases are available online through the Entrez search engine.
An integrated publicly accessible bioinformatics resource to support genomic/proteomic research and scientific discovery.
Established in 1984, by the National Biomedical Research Foundation (NBRF) Georgetown University Medial Center, Washington D.C., USA.
It is the source of annotated protein databases and analysis tools for the researchers.
Serve as primary resource for the exploration of protein information.
Accessible by text search for entry and list retrieval, and also BLAST search and peptide match.
The Protein Data Bank (PDB) is a database for the three-dimensional structural data of large biological molecules, such as proteins and nucleic acids. This presentation deals with what, why, how, where and who of PDB. In this presentation we have also included briefing about various file formats available in PDB with emphasis on PDB file format
Scoring system is a set of values for qualifying the set of one residue being substituted by another in an alignment.
It is also known as substitution matrix.
Scoring matrix of nucleotide is relatively simple.
A positive value or a high score is given for a match & negative value or a low score is given for a mismatch.
Scoring matrices for amino acids are more complicated because scoring has to reflect the physicochemical properties of amino acid residues.
Sequence alig Sequence Alignment Pairwise alignment:-naveed ul mushtaq
Sequence Alignment Pairwise alignment:- Global Alignment and Local AlignmentTwo types of alignment Progressive Programs for multiple sequence alignment BLOSUM Point accepted mutation (PAM)PAM VS BLOSUM
This presentation gives you a detailed information about the swiss prot database that comes under UniProtKB. It also covers TrEMBL: a computer annotated supplement to Swiss-Prot.
The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA sequences. It is located at the National Institute of Genetics (NIG) in the Shizuoka prefecture of Japan. It is also a member of the International Nucleotide Sequence Database Collaboration or INSDC.
Bioinformatics in biotechnology by kk sahu KAUSHAL SAHU
Introduction
Bioinformatics – definition
History
Required skills
Core areas of bioinformatics
Components of bioinformatics
Nomenclature system in bioinformatics
Biological databases
Types of database
Bioinformatics tools
Applications of bioinformatics
Conclusion
References
BIOLOGICAL DATABASES :
A biological database is a large, organized body of persistent data, usually associated with computerized software designed to update, query, and retrieve components of the data stored within the system.
The chief objective of the development of a database is to organize data in a set of structured records to enable easy retrieval of information.
Example. A few popular databases are GenBank from NCBI (National Center for Biotechnology Information), SwissProt from the Swiss Institute of Bioinformatics and PIR from the Protein Information Resource.
IMPORTANCE OF DATABASES :
1. Databases act as a store house of information.
2. Databases are used to store and organize data in such a way that information can be retrieved easily via a variety of search criteria.
3. It allows knowledge discovery, which refers to the identification of connections between pieces of information that were not known when the information was first entered. This facilitates the discovery of new biological insights from raw data.
4. Secondary databases have become the molecular biologist’s reference library over the past decade or so, providing a wealth of information on just about any gene or gene product that has been investigated by the research community.
5. It helps to solve cases where many users want to access the same entries of data.
6. Allows the indexing of data.
7. It helps to remove redundancy of data.
TYPES OF BIOLOGICAL DATABASES:
Biological databases are classified on
1. Based on content of biological data
2. Based on the nature of data.
1. BASED ON CONTENT OF BIOLOGICAL DATA :
Based on their contents, biological databases can be roughly divided into two categories:
1. Primary databases
2. Secondary databases
An integrated publicly accessible bioinformatics resource to support genomic/proteomic research and scientific discovery.
Established in 1984, by the National Biomedical Research Foundation (NBRF) Georgetown University Medial Center, Washington D.C., USA.
It is the source of annotated protein databases and analysis tools for the researchers.
Serve as primary resource for the exploration of protein information.
Accessible by text search for entry and list retrieval, and also BLAST search and peptide match.
The Protein Data Bank (PDB) is a database for the three-dimensional structural data of large biological molecules, such as proteins and nucleic acids. This presentation deals with what, why, how, where and who of PDB. In this presentation we have also included briefing about various file formats available in PDB with emphasis on PDB file format
Scoring system is a set of values for qualifying the set of one residue being substituted by another in an alignment.
It is also known as substitution matrix.
Scoring matrix of nucleotide is relatively simple.
A positive value or a high score is given for a match & negative value or a low score is given for a mismatch.
Scoring matrices for amino acids are more complicated because scoring has to reflect the physicochemical properties of amino acid residues.
Sequence alig Sequence Alignment Pairwise alignment:-naveed ul mushtaq
Sequence Alignment Pairwise alignment:- Global Alignment and Local AlignmentTwo types of alignment Progressive Programs for multiple sequence alignment BLOSUM Point accepted mutation (PAM)PAM VS BLOSUM
This presentation gives you a detailed information about the swiss prot database that comes under UniProtKB. It also covers TrEMBL: a computer annotated supplement to Swiss-Prot.
The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA sequences. It is located at the National Institute of Genetics (NIG) in the Shizuoka prefecture of Japan. It is also a member of the International Nucleotide Sequence Database Collaboration or INSDC.
Bioinformatics in biotechnology by kk sahu KAUSHAL SAHU
Introduction
Bioinformatics – definition
History
Required skills
Core areas of bioinformatics
Components of bioinformatics
Nomenclature system in bioinformatics
Biological databases
Types of database
Bioinformatics tools
Applications of bioinformatics
Conclusion
References
BIOLOGICAL DATABASES :
A biological database is a large, organized body of persistent data, usually associated with computerized software designed to update, query, and retrieve components of the data stored within the system.
The chief objective of the development of a database is to organize data in a set of structured records to enable easy retrieval of information.
Example. A few popular databases are GenBank from NCBI (National Center for Biotechnology Information), SwissProt from the Swiss Institute of Bioinformatics and PIR from the Protein Information Resource.
IMPORTANCE OF DATABASES :
1. Databases act as a store house of information.
2. Databases are used to store and organize data in such a way that information can be retrieved easily via a variety of search criteria.
3. It allows knowledge discovery, which refers to the identification of connections between pieces of information that were not known when the information was first entered. This facilitates the discovery of new biological insights from raw data.
4. Secondary databases have become the molecular biologist’s reference library over the past decade or so, providing a wealth of information on just about any gene or gene product that has been investigated by the research community.
5. It helps to solve cases where many users want to access the same entries of data.
6. Allows the indexing of data.
7. It helps to remove redundancy of data.
TYPES OF BIOLOGICAL DATABASES:
Biological databases are classified on
1. Based on content of biological data
2. Based on the nature of data.
1. BASED ON CONTENT OF BIOLOGICAL DATA :
Based on their contents, biological databases can be roughly divided into two categories:
1. Primary databases
2. Secondary databases
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret the biological data.
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 aventures in two entangled wonderlandsRichard 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.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
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.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
2. A database is a repository of sequence ( DNA or amino acids ) stored in a
computer which provide a centralized and homogenous view of its content.
or, it is a vast collection of data pertaining to a specific topic, e.g.,
nucleotide sequence, protein sequence etc.
Basically, it is an electronic environment.
Databases are at the heart of bioinformatics.
3. 1. Sequence databases: - that involves the sequences of both proteins and nucleic
acids.
2. Structural databases:- that involves only protein databases.
In additionally, it is also classified into three categories:
A. Primary database B. Secondary databases C. Composite databases.
4. It contain information of the sequence or structure alone either protein or
nucleic acid .
Example: PIR, SWISS-PROT for protein sequences , NCBI, EMBL and DDBJ for
genome sequences.
5. PIR: It is functionally annotated
protein sequences and structure.
PIR has collaborated with EBI and
SIB to establish the UniProt (
United Protein Databases).
The central resource of
protein sequence and function.
7. NCBI ( National Centre of Biotechnology Information ):
- Nov 4, 1988 , the NCBI was established as division of the National Library of medicine for the
development of information systems in molecular biology.
- The NCBI is located in Bethesta, Maryland (U.S.A).
- NCBI built the GenBank, which is an annotated collection of publically available nucleotide and
protein sequences.
- In 1988, the three partners (DDBJ, EMBL and GenBank) of the international Nucelotide
Sequences Database collaboration had a meeting and agreed to use a common format.
8. i. Maintains collaboration with several NIH institutes, academia, industry and other governmental
agencies.
ii. Develops, distributes, supports and coordinates access to a variety of databases and software for
the scientific and medical communities.
iii. Develops and promotes standards for databases, data deposition and exchange, and biological
nomenclature.
iv. Engages the members of the international scientific community in informatics research and training
through the scientific visitors programs.
Link: https://www.ncbi.nlm.nih.gov/
9. In 1992, NCBI has the responsibility for making available the
DNA sequence database to the GenBank.
Coordinates with individual laboratories and other sequence
data base such those of EMBL and DDBJ.
Moreover, NCBI has grown to provide other databases in
addition to GenBank.
GenBank is a comprehensive sequence database that contains
publicly available DNA sequences for more than 1,19,000
different organisms obtained through the submission of
sequence data from individual lab and batch submissions from
large-scale of seq. projects.
Daily data exchange with the EMBL data library in the UK and
the DNA Data Bank of Japan helps world wide coverage.
10. Developed and maintained by European Molecular Biology Laboratory – European
Bioinformatics Institute (EMBL-EBI).
Comprehensive data nucleotide sequence information.
11. The European Molecular Biology Laboratory (EMBL) Nucleotide Sequence Database is a
comprehensive collection of primary nucleotide sequences maintained at the European
Bioinformatics Institute (EBI).
Link: http:www.ebi.ac.uk/embl/
EMBL is supported by 22 member states, four prospect, and two associated states.
The laboratory operatory operates from five sites: the main laboratory in Heidelberg, and
outstations Hinxton (EBI, in England), Grenoble (France), Hambury (Germany) and
Manterotando ( near Rome).
12. EMBL groups and laboratories perform basic research in molecular biology and molecular
medicine as well as training for science student and visitors.
Since 1982 this work has been done in collaboration with GenBank (NCBI, Bethesda, USA)
and the DNA Database of Japan (Mishima).
For sequencing similar searching, a variety of tools (FASTA and BLAST
are available that allow external users to compare their own seq. against the data in
EMBL nucleotide sequence database and other database.
13. The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA
sequences. It was established in 1986.
Link: https://www.ddbj.nig.ac.jp
It is located at the National Institute of Genetics (NIG) in the Shizuoka prefecture of
Japan.
DDBJ is a member of the International Nucleotide Sequence Database
Collaboration or INSDC.
It exchanges its data with European Molecular Biology Laboratory at the European
Bioinformatics Institute and with GenBank at the National Center for Biotechnology
Information on a daily basis.
14. DDBJ Center collects nucleotide sequence data as a member of INSDC(International
Nucleotide Sequence Database Collaboration) and provides freely available nucleotide
sequence data and supercomputer system, to support research activities in life science.
FEATURES
group 1: biological source of the sequence (source) The feature, “source” (group 1) is
mandatory for all entries in the international nucleotide database. ...
group 2: biological function features of the region. ...
group 3: difference and/or change of the sequence data.
15. Data type Organism Accession numbers for annotated
sequences (number of entries)
Accession numbers for raw reads
Genome Radish (Raphanus sativus cv. Aokubi S-
h)
WGS: BAOO01000001-
BAOO01072909 (72 909 entries)
scaffold CON: DF196826-
DF236948 (40,123 entries)
DRR012610-DRR012624
Soybean (Glycine max cv. Enrei) BBNX02000001-BBNX02108601 (108
601 entries)
DRR021740-DRR021744
Common marmoset (Callithrix jacchus) WGS: BBXK01000001-
BBXK01109198 (109 198 entries)
scaffold CON: DG000097-
DG000120 (24 entries)
GSS: LB274659-LB427105 (152 447
entries)
DRR036754-DRR036764
List of notable data sets released from the DNA Data Bank of Japan (DDBJ) sequence databases from June 2015 to May 2016
16. Hosted at National Institute of Genetics .
Mainly from scientists in Japan and also from resources all over the world and shave this
nucleotide data with EMBL and GenBank.
This officially , certified to collect nucleotide sequence from researchers sand to tissue the
internationally recognized number of data submitters.
About 99% of the nucleotide data in INSDC are submitted by DDMJ
This database plays a major role to improve the quality of INSDC.
Each database entry include details of sequences, submitters details bibiliographic
references, biological significance and the scientific name and taxonomy of the organism.
17. Features that identify coding regions transcription units, mutation sites etc. are displayed
in a feature table. Major activities of the database.
Providing internationally recognized accession numbers to sequences.
Bioinformatics database management developing tools for the analysis and visualization of
biological data.
Conducting courses for beginners to reduce the complexity in the biological data analysis.