SWISS-PROT- Protein Database- The Universal Protein Resource Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins.
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 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
SWISS-PROT- Protein Database- The Universal Protein Resource Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins.
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 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
INTRODUCTION
WHAT IS DATA AND DATABASE?
WHAT IS BIOLOGICAL DATABASE?
TYPES OF BIOLOGICAL DATABASE
PRIMARY DATABASE
Nucleic acid sequence database
Protein sequence database
SECONDARY DATABASE
COMPOSITE DATABASE
TERTIARY DATABASE
WHY NEED?
CONCLUSION
REFRENCES
INTRODUCTION
DEFINITION OF BIOINFORMATICS
HISTORY
OBJECTIVES OF BIOINFORMATICS
TOOLS OF BIOINFORMATICS
BIOLOGICAL DATABASES
HOMOLOGY AND SIMILARITY TOOLS (SEQUENCE ALIGNMENT)
PROTEIN FUNCTION ANALYSIS TOOLS
STRUCTURAL ANALYSIS TOOLS
SEQUENCE MANIPULATION TOOLS
SEQUENCE ANALYSIS TOOLS
APPLICATION
CONCLUSION
REFERENCES
Lecture delivered by T. Ashok Kumar, Head, Department of Bioinformatics, Noorul Islam College of Arts and Science, Kumaracoil, Thuckalay, INDIA. UGC Sponsored National Workshop on BIOINFORMATICS AND GENOME ANALYSIS for College Teachers on August 11 & 12, 2014. Organized by Centre for Bioinformatics, Department of Zoology, NMCC.
INTRODUCTION
WHAT IS DATA AND DATABASE?
WHAT IS BIOLOGICAL DATABASE?
TYPES OF BIOLOGICAL DATABASE
PRIMARY DATABASE
Nucleic acid sequence database
Protein sequence database
SECONDARY DATABASE
COMPOSITE DATABASE
TERTIARY DATABASE
WHY NEED?
CONCLUSION
REFRENCES
INTRODUCTION
DEFINITION OF BIOINFORMATICS
HISTORY
OBJECTIVES OF BIOINFORMATICS
TOOLS OF BIOINFORMATICS
BIOLOGICAL DATABASES
HOMOLOGY AND SIMILARITY TOOLS (SEQUENCE ALIGNMENT)
PROTEIN FUNCTION ANALYSIS TOOLS
STRUCTURAL ANALYSIS TOOLS
SEQUENCE MANIPULATION TOOLS
SEQUENCE ANALYSIS TOOLS
APPLICATION
CONCLUSION
REFERENCES
Lecture delivered by T. Ashok Kumar, Head, Department of Bioinformatics, Noorul Islam College of Arts and Science, Kumaracoil, Thuckalay, INDIA. UGC Sponsored National Workshop on BIOINFORMATICS AND GENOME ANALYSIS for College Teachers on August 11 & 12, 2014. Organized by Centre for Bioinformatics, Department of Zoology, NMCC.
BIOINFORMATICS AND DATABASES IN BIOINFORMATICS.pdfPravanjanDash
BIOLOGICAL DATABASES are
Collection of files containing records of biological data in machine readable form Can be accessed, added, retrieved, manipulated and modified.
COMPUNATIONAL BIOLOGY AND DATABASES IN BIOINFORMATICS.pptxPravanjanDash
BIOLOGICAL DATABASES are
Collection of files containing records of biological data in machine readable form Can be accessed, added, retrieved, manipulated and modified.
In the era of computers life sciences databases are still understated. Here is my presentation on biological databases. Complete classification of different databases.
For more presentations and work come and visit
https://www.linkedin.com/in/shradheya-r-r-gupta-54492984/
Bioinformatics is defined as the application of tools of computation and analysis to the capture and interpretation of biological data. It is an interdisciplinary field, which harnesses computer science, mathematics, physics, and biology
ANALYSIS OF PROTEIN MICROARRAY DATA USING DATA MININGijbbjournal
Latest progress in biology, medical science, bioinformatics, and biotechnology has become important and
tremendous amounts of biodata that demands in-depth analysis. On the other hand, recent progress in data
mining research has led to the development of numerous efficient and scalable methods for mining
interesting patterns in large databases. This paper bridge the two fields, data mining and bioinformatics
for successful mining of biological data. Microarrays constitute a new platform which allows the discovery
and characterization of proteins.
Bioinformatics databases: Current Trends and Future PerspectivesUniversity of Malaya
Data is the most powerful resource in any field or subject of study. In Biology, data comes from scientists and their actions, while any institution that makes sense of the data collected, will be in the forefront in their respective research field. In the beginning of any data collection endeavour, it is critical to find proper management techniques to store data and to maximise its utilisation. This presentation reflects upon the current trends and techniques of data modeling, architecture with a highlight on the uses of database, focusing on Bioinformatics examples and case studies. Finally, the future of bioinformatics databases is highlighted to give an overview of the modeling techniques to accommodate the biological data escalation in coming years.
Semantic Web & Web 3.0 empowering real world outcomes in biomedical research ...Amit Sheth
Talk presented in Spain (WiMS 2013/UAM-Madrid, UMA-Malaga), June 2013.
Replaces earlier version at: http://www.slideshare.net/apsheth/semantic-technology-empowering-real-world-outcomes-in-biomedical-research-and-clinical-practices
Biomedical and translational research as well as clinical practice are increasingly data driven. Activities routinely involve large number of devices, data and people, resulting in the challenges associated with volume, velocity (change), variety (heterogeneity) and veracity (provenance, quality). Equally important is to realize the challenge of serving the needs of broader ecosystems of people and organizations, extending traditional stakeholders like drug makers, clinicians and policy makers, to increasingly technology savvy and information empowered patients. We believe that semantics is becoming centerpiece of informatics solutions that convert data into meaningful, contextually relevant information and insights that lead to optimal decisions for translational research and 360 degree health, fitness and well-being.
In this talk, I will provide a series of snapshots of efforts in which semantic approach and technology is the key enabler. I will emphasize real-world and in-use projects, technologies and systems, involving significant collaborations between my team and biomedical researchers or practicing clinicians. Examples include:
• Active Semantic Electronic Medical Record
• Semantics and Services enabled Problem Solving Environment for T.cruzi (SPSE)
• Data Mining of Cardiology data
• Semantic Search, Browsing and Literature Based Discovery
• PREscription Drug abuse Online Surveillance and Epidemiology (PREDOSE)
• kHealth: development of a knowledge-enhanced sensing and mobile computing applications (using low cost sensors and smartphone), along with ability to convert low level observations into clinically relevant abstractions
Further details are at http://knoesis.org/amit/hcls
Protein sequence classification in data mining– a studyZac Darcy
Since the computerized applications are used all around the world, there occurs the c
ollection of a vast
amount of data
. The important information hidden in vast data is attracting the researchers of multiple
disciplines to make study in developing effective approaches to derive the hidden knowledge within them.
Data mining
may be
considered
to be
the process of extracting
or mining
the useful
and valuable
knowledge from large amounts of data. There
are various different domains in data mining such as text
mining, image mining, sequential pattern
mining, web mining and etc. Among these, sequence mining is
one of the most im
portant research area
which helps to finding the sequential relationships found in the
data.
Sequence mining is applied in
wide range of application
areas such as the analysis of customer
purchase patterns, web access patterns, weather
observations, protei
n sequencing, DNA sequencing, etc. In
protein and DNA analysis, sequence mining
techniques are used for sequence alignment, sequence
searching and sequence classification. In
the area of
protein
sequence analysis, the researchers are
showing their interest
in the field of protein sequence
classification. It has the
ability to discover the
recurring structures that exist in
the
protein
sequences. This paper explains various techniques used by
different researchers in classifying the proteins and also provide
s an overview of different protein sequence
classification methods
PROTEIN SEQUENCE CLASSIFICATION IN DATA MINING– A STUDYZac Darcy
Since the computerized applications are used all around the world, there occurs the collection of a vast
amount of data. The important information hidden in vast data is attracting the researchers of multiple
disciplines to make study in developing effective approaches to derive the hidden knowledge within them.
Data mining may be considered to be the process of extracting or mining the useful and valuable
knowledge from large amounts of data. There are various different domains in data mining such as text
mining, image mining, sequential pattern mining, web mining and etc. Among these, sequence mining is
one of the most important research area which helps to finding the sequential relationships found in the
data. Sequence mining is applied in wide range of application areas such as the analysis of customer
purchase patterns, web access patterns, weather observations, protein sequencing, DNA sequencing, etc. In
protein and DNA analysis, sequence mining techniques are used for sequence alignment, sequence
searching and sequence classification. In the area of protein sequence analysis, the researchers are
showing their interest in the field of protein sequence classification. It has the ability to discover the
recurring structures that exist in the protein sequences. This paper explains various techniques used by
different researchers in classifying the proteins and also provides an overview of different protein sequence
classification methods.
Protein Sequence Classification In Data Mining - A StudyZac Darcy
Since the computerized applications are used all around the world, there occurs the collection of a vast
amount of data. The important information hidden in vast data is attracting the researchers of multiple
disciplines to make study in developing effective approaches to derive the hidden knowledge within them.
Data mining may be considered to be the process of extracting or mining the useful and valuable
knowledge from large amounts of data. There are various different domains in data mining such as text
mining, image mining, sequential pattern mining, web mining and etc. Among these, sequence mining is
one of the most important research area which helps to finding the sequential relationships found in the
data. Sequence mining is applied in wide range of application areas such as the analysis of customer
purchase patterns, web access patterns, weather observations, protein sequencing, DNA sequencing, etc. In
protein and DNA analysis, sequence mining techniques are used for sequence alignment, sequence
searching and sequence classification. In the area of protein sequence analysis, the researchers are
showing their interest in the field of protein sequence classification. It has the ability to discover the
recurring structures that exist in the protein sequences. This paper explains various techniques used by
different researchers in classifying the proteins and also provides an overview of different protein sequence
classification methods.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
1. Submitted by: SOMBIR SINGH
Research Scholar
Center for Biotechnology
MD University Rohtak Haryana
sombirkumar9195@gmail.com
2. BIOLOGICAL DATABASE
A collection of data that is structured, searchable,
updated periodically and cross-referenced.
Store biological data in electronic form
Purpose-
systemization of database
availability of biological data
analysis of computed biological data
3. FEATURES OF BIOLOGICAL
DATABASE
Heterogeneity
High volume data
Uncertainity
Data curation
Data integration
Data sharing
Dynamics
4. 1. Data heterogeneity
Availabilty of diverse and complex data types.
Data types:
sequence- nucleotide, protein
graph- data indicating relationship among
themselves can be captured as graph. It include
pathway data, genetic maps and structural texonomy.
5. high dimensional data- data generated from micro-
array experiments that involve thousands of genes and
hundreds of experimental conditions.
shapes- consists of 3D molecular structural data.
temporal data- for studing dynamics of any
biological system. Example- development biology.
6. Patterns- there are patterns lying within the genome
that characterize biologically entities. example-
regulatory sequence
Scalar and vector fields
Extracted features data- numerical data obtained
from combination of one of the above mentioned data
types.
7. 2. High volume data- in addition to being highly
heterogeneous, biological data are voluminous to
support comprehensive investigations in various field
and directions.
3. Uncertainity- biological data have great deal of
uncertainity as they represent biological phenomena
that are observed and assumed.
8. 4. Data curation- biological data collected from various
sources across different and functional boundaries.
There are always chances of missing links.
To fill these, the data is analyzed and curated via
automated methods.
9. 5. Data integration- after years of research, across
different structural and functional scales, data is
collected from laboratories through a database and
made available for use.
10. 6. Data sharing- biological data is share via databases.
Purpose:
for scientific community’s inspection
for cross verification
to prevent repetition and validation of data
11. Dynamics-
new data is generated every day in laboratories.
sometimes this new data contradicts with the old data
so, it is necessary to develop new organizational
database schemes to incorporate new data.
17. 3. Data access
Publicly available
Available with copyright
Browsing only, accessible but not downloadable
Academic but not freely available
Restricted
18. 4. DATA SOURCE
a) primary database
original data submission by researcher occurs.
Examples:
Nucleotide - genBank, EMBL, DDBJ
Protein - UniProt
Structure – PDB
Literature - PubMed
b) Secondary database
- results of analysis of primary databases.
- either manually curated or by automated methods
examples: Prosite, Pfam, RefSeq
