Molecular visualization
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Looking at molecular models in order to explore and understand them. Does not necessarily involve molecular modeling (changing the existing model). Macromolecules – Protein, DNA, RNA, or their complexes. 3-D view of different molecules on the computer.
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Kegg
The document describes several key databases within the KEGG resource, including:
- The PATHWAY database containing molecular network maps of metabolic and genetic pathways.
- The BRITE database providing hierarchical classifications of biological systems beyond what is shown in pathways.
- The LIGAND database consisting of chemical compounds, carbohydrates, reactions, and enzyme information.
KEGG aims to comprehensively capture biological knowledge through integrated databases covering genomes, pathways, diseases and drugs.
Structural databases
Structural databases like PDB, CSD, and CATH contain 3D structural information of proteins, small molecules, and macromolecules determined through techniques like X-ray crystallography and NMR spectroscopy. These databases provide bibliographic data, atomic coordinates, and other details for each entry. PDB contains protein structures, CSD contains organic and metal-organic structures, and CATH classifies protein domains hierarchically. Structural databases have wide applications in structure prediction, analysis, mining, comparison, classification, structure refinement, and database annotation.
Scop database
The SCOP database classifies protein structures hierarchically and describes evolutionary relationships between proteins. It was created in 1994 at the Centre for Protein Engineering and is maintained manually. SCOP links to the Protein Data Bank to obtain structural classifications for each protein structure directly and can also be searched to find a protein's structural class, fold, and domain information.
PIR- Protein Information Resource
PIR- Protein Information ResourceThapar Institute of Engineering & Technology, Patiala, Punjab, India
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.
Protein data bank
The Protein Data Bank (PDB) is an open database that archives 3D structural data of biological macromolecules. It was established in 1971 and currently holds over 150,000 structures determined by X-ray crystallography or NMR spectroscopy. The PDB is overseen by the Worldwide Protein Data Bank and freely accessible online. It serves as a key resource for structural biology and many other databases rely on protein structures deposited in the PDB.
Protein data bank
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
Clustal
Clustal Omega is a fast and scalable program for multiple sequence alignment. It begins by producing pairwise alignments using a word-based heuristic method. It then clusters the sequences using a modified mBed distance method and k-means clustering. Finally, it generates the multiple sequence alignment using the HHAlign package, which aligns profile HMMs built from the sequences. Clustal Omega is widely considered one of the fastest online multiple sequence alignment tools.
Proteins databases
This document provides an overview of protein databases. It discusses the importance of protein databases for storing and analyzing protein sequence, structure, and functional data generated by modern biology. It summarizes several major public protein databases, including UniProt, NCBI RefSeq, PDB, InterPro, and Pfam, which contain protein sequences, structures, families, domains, and functional annotations. Searching and comparing sequences in these databases is an important first step in studying new proteins.
Recommended
Kegg
The document describes several key databases within the KEGG resource, including:
- The PATHWAY database containing molecular network maps of metabolic and genetic pathways.
- The BRITE database providing hierarchical classifications of biological systems beyond what is shown in pathways.
- The LIGAND database consisting of chemical compounds, carbohydrates, reactions, and enzyme information.
KEGG aims to comprehensively capture biological knowledge through integrated databases covering genomes, pathways, diseases and drugs.
Structural databases
Structural databases like PDB, CSD, and CATH contain 3D structural information of proteins, small molecules, and macromolecules determined through techniques like X-ray crystallography and NMR spectroscopy. These databases provide bibliographic data, atomic coordinates, and other details for each entry. PDB contains protein structures, CSD contains organic and metal-organic structures, and CATH classifies protein domains hierarchically. Structural databases have wide applications in structure prediction, analysis, mining, comparison, classification, structure refinement, and database annotation.
Scop database
The SCOP database classifies protein structures hierarchically and describes evolutionary relationships between proteins. It was created in 1994 at the Centre for Protein Engineering and is maintained manually. SCOP links to the Protein Data Bank to obtain structural classifications for each protein structure directly and can also be searched to find a protein's structural class, fold, and domain information.
PIR- Protein Information Resource
PIR- Protein Information ResourceThapar Institute of Engineering & Technology, Patiala, Punjab, India
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.
Protein data bank
The Protein Data Bank (PDB) is an open database that archives 3D structural data of biological macromolecules. It was established in 1971 and currently holds over 150,000 structures determined by X-ray crystallography or NMR spectroscopy. The PDB is overseen by the Worldwide Protein Data Bank and freely accessible online. It serves as a key resource for structural biology and many other databases rely on protein structures deposited in the PDB.
Protein data bank
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
Clustal
Clustal Omega is a fast and scalable program for multiple sequence alignment. It begins by producing pairwise alignments using a word-based heuristic method. It then clusters the sequences using a modified mBed distance method and k-means clustering. Finally, it generates the multiple sequence alignment using the HHAlign package, which aligns profile HMMs built from the sequences. Clustal Omega is widely considered one of the fastest online multiple sequence alignment tools.
Proteins databases
This document provides an overview of protein databases. It discusses the importance of protein databases for storing and analyzing protein sequence, structure, and functional data generated by modern biology. It summarizes several major public protein databases, including UniProt, NCBI RefSeq, PDB, InterPro, and Pfam, which contain protein sequences, structures, families, domains, and functional annotations. Searching and comparing sequences in these databases is an important first step in studying new proteins.
Swiss pdb viewer
Swiss-PdbViewer is an application that provides a user-friendly interface allowing to analyze several proteins at the same time.
Protein protein interactions
The document discusses protein-protein interactions (PPIs) and methods used to study them. It defines PPIs as physical contacts between two or more proteins through biochemical or electrostatic forces. It describes different types of PPIs including homo-oligomers, hetero-oligomers, covalent and non-covalent interactions. Common methods to study PPIs are also summarized, such as yeast two-hybrid systems, co-immunoprecipitation, and protein interaction databases. The applications and importance of PPI research are mentioned including roles in various cellular processes and diseases.
UniProt
UniProt is a comprehensive database of protein sequences and functional information that is curated by the European Bioinformatics Institute, SIB Swiss Institute of Bioinformatics, and the Protein Information Resource. It contains three main components: UniProtKB for functional information, UniRef for clustered sequences, and UniParc for comprehensive protein sequences. As genome sequencing increases, UniProt provides centralized storage and interconnection of protein data from various sources to further scientific understanding of proteins.
Swiss pdb viewer
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NCBI National Center for Biotechnology Information
NCBI National Center for Biotechnology InformationThapar Institute of Engineering & Technology, Patiala, Punjab, India
The National Center for Biotechnology Information advances science and health by providing access to biomedical and genomic informationBioinformatics data mining
Data mining involves using machine learning and statistical methods to discover patterns in large datasets and is useful in bioinformatics for analyzing biological data. Bioinformatics analyzes data from sequences, molecules, gene expressions, and pathways. Data mining can help understand these rapidly growing biological datasets. Common data mining tools in bioinformatics include BLAST for sequence comparisons, Entrez for integrated database searching, and ORF Finder for identifying open reading frames. Data mining approaches are well-suited to the enormous volumes of data in bioinformatics databases.
Dot matrix
This document discusses sequence alignment methods. It describes dot matrix analysis which compares sequences by placing dots where characters match in a grid. Global alignment aims to align entire sequences while local focuses on matching stretches. Filtering removes random matches. The Protein Data Bank is a repository of 3D protein and nucleic acid structures identified by unique 4-character codes.
BLAST
This document discusses the Basic Local Alignment Search Tool (BLAST), which allows users to compare a query DNA or protein sequence against sequence databases to find regions of local similarity. BLAST breaks the query into short words that are then searched for in database sequences. When words are found in common, BLAST extends the alignment in both directions to find higher-scoring matches. BLAST outputs include a graphical display of alignments, a hit list ranking matches by similarity score, and detailed alignments. BLAST has many applications, such as identifying species, establishing evolutionary relationships, DNA mapping, and locating protein domains.
European molecular biology laboratory (EMBL)
European Molecular Biology Laboratory (EMBL) is one of the biggest database related to bioinformatics research work.
Molecular modeling database
The Molecular Modeling Database (MMDB) is a database hosted by the National Center for Biotechnology Information that contains over 28,000 experimentally determined 3D structures of biomolecules including proteins and nucleic acids derived from the Protein Data Bank, excluding theoretical models. It facilitates computation and links structures to other data types. Each record cross-references its source PDB file. The database contains molecular structures, biological activity data, experimental data, chemical properties, and annotations to aid researchers. Examples of widely used molecular modeling databases discussed are the Protein Data Bank, PubChem, and RCSB Ligand Explorer.
MULTIPLE SEQUENCE ALIGNMENT
This document discusses multiple sequence alignment techniques. It begins with definitions of key terms like homology, similarity, and conservation. It then describes pairwise alignment and its applications. The rest of the document focuses on multiple sequence alignment methods like progressive alignment, iterative refinement, tree alignment, star alignment, and using genetic algorithms. It provides examples and explanations of popular multiple sequence alignment tools like Clustal W and T-Coffee.
Ab Initio Protein Structure Prediction
Ab initio protein structure prediction uses computational methods to predict a protein's 3D structure from its amino acid sequence. It relies on conformational searching to generate structure decoys and selecting native-like models. The key factors for success are an accurate energy function, efficient search methods like molecular dynamics or genetic algorithms, and effective selection of models close to the native structure. Model selection approaches include energy evaluations, compatibility scores, clustering of similar decoys, and identifying the lowest energy conformations.
Uni prot presentation
UniProt is a comprehensive, freely accessible database that is a central repository for protein data. It is produced through collaboration between the European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. UniProt contains protein sequences, functional information, evolutionary data, and details about biological processes, post-translational modifications, interactions, and subcellular locations to characterize proteins.
Biological databases
This document summarizes different types of biological data and biological databases. It discusses primary databases like GenBank, EMBL and DDBJ that contain raw nucleotide sequence data. Secondary databases like KEGG and Pfam analyze and annotate primary database content. Composite databases like NCBI aggregate data from multiple primary sources. Protein databases discussed include Swiss-Prot, TrEMBL, PDB, and Pfam. Structural databases such as SCOP, CATH and PDB organize protein structures.
Kegg databse
Rashi Srivastava presented on the KEGG database in biotechnology. KEGG is a database that contains genomic, chemical, and systems information to understand biological functions from the molecular level up. It includes pathways, genes, compounds, diseases, drugs, and organisms. KEGG can be searched through its flat file format using DBGET or through its relational database format for more complex queries. It also contains the KEGG MEDICUS search tool and direct SQL searches of its relational database.
Protein protein interaction
Protein-protein interactions are important for many biological processes. There are various types of interactions depending on their composition and duration. Methods to study interactions include yeast two-hybrid, co-immunoprecipitation, affinity chromatography, and chromatin immunoprecipitation. Databases such as IntAct and MINT provide repositories for protein interaction data.
Multiple sequence alignment
Multiple sequence alignment (MSA) aligns three or more biological sequences, like proteins or nucleic acids, to infer homology and evolutionary relationships. There are three main methods - dynamic programming computes an optimal alignment but has high runtime; progressive alignment first does pairwise alignments and adds sequences; iterative alignment successively improves approximations without pairwise alignments. Popular tools for MSA include Clustal W, MAFFT, MUSCLE, and T-Coffee. MSA helps detect similarities, conserved motifs, and structural homologies between sequences.
Rasmol
Rasmol and Swiss-PDB viewer are molecular visualization tools that allow users to view and analyze protein structures. Rasmol can display molecules in various representations like wireframe, cylinders, or ribbons. It supports common file formats like PDB and can rotate, zoom, and translate structures. Swiss-PDB viewer is tightly integrated with homology modeling and allows users to build models, compare structures, and view electron density maps. It utilizes template structures from the PDB to generate models and assess their quality. Both tools provide publication-quality images and interactive visualization of biomolecular structures.
Protein database
This document provides an overview of several important protein databases:
- SWISS-PROT is an annotated protein sequence database that is maintained collaboratively and contains over 1.29 million entries. TrEMBL is a computer-annotated supplement to SWISS-PROT containing sequences not yet in SWISS-PROT.
- Structural databases like PDB, SCOP, and CATH provide protein structure information. PDB is an international repository for macromolecular structures. SCOP and CATH classify protein domains based on structural similarities and evolutionary relationships.
- Other databases mentioned include InterPro, GOA, Proteome Analysis, and GenBank, which provide functional annotation, gene ontology assignments, proteome analysis
Gene prediction methods vijay
Automated sequencing of genomes require automated gene assignment
Includes detection of open reading frames (ORFs)
Identification of the introns and exons
Gene prediction a very difficult problem in pattern recognition
Coding regions generally do not have conserved sequences
Much progress made with prokaryotic gene prediction
Eukaryotic genes more difficult to predict correctly
Computational Analysis with ICM
This document discusses using computational tools like Interactive Chromatin Modeling (ICM) and the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to model chromatin structure and behavior. ICM allows generating chromatin templates based on DNA sequence and known nucleosome positioning. LAMMPS is then used to simulate the chromatin structures generated by ICM and minimize collisions between molecules. The goal is to better understand chromatin packing and dynamics through computational modeling and analysis.
Homology modelling
Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
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The document discusses protein-protein interactions (PPIs) and methods used to study them. It defines PPIs as physical contacts between two or more proteins through biochemical or electrostatic forces. It describes different types of PPIs including homo-oligomers, hetero-oligomers, covalent and non-covalent interactions. Common methods to study PPIs are also summarized, such as yeast two-hybrid systems, co-immunoprecipitation, and protein interaction databases. The applications and importance of PPI research are mentioned including roles in various cellular processes and diseases.
UniProt
UniProt is a comprehensive database of protein sequences and functional information that is curated by the European Bioinformatics Institute, SIB Swiss Institute of Bioinformatics, and the Protein Information Resource. It contains three main components: UniProtKB for functional information, UniRef for clustered sequences, and UniParc for comprehensive protein sequences. As genome sequencing increases, UniProt provides centralized storage and interconnection of protein data from various sources to further scientific understanding of proteins.
Swiss pdb viewer
Swiss PDB viewer by sivasangari Shanmugam. The protein data bank is a repository for the 3-D structural data of large biological molecules
NCBI National Center for Biotechnology Information
NCBI National Center for Biotechnology InformationThapar Institute of Engineering & Technology, Patiala, Punjab, India
The National Center for Biotechnology Information advances science and health by providing access to biomedical and genomic informationBioinformatics data mining
Data mining involves using machine learning and statistical methods to discover patterns in large datasets and is useful in bioinformatics for analyzing biological data. Bioinformatics analyzes data from sequences, molecules, gene expressions, and pathways. Data mining can help understand these rapidly growing biological datasets. Common data mining tools in bioinformatics include BLAST for sequence comparisons, Entrez for integrated database searching, and ORF Finder for identifying open reading frames. Data mining approaches are well-suited to the enormous volumes of data in bioinformatics databases.
Dot matrix
This document discusses sequence alignment methods. It describes dot matrix analysis which compares sequences by placing dots where characters match in a grid. Global alignment aims to align entire sequences while local focuses on matching stretches. Filtering removes random matches. The Protein Data Bank is a repository of 3D protein and nucleic acid structures identified by unique 4-character codes.
BLAST
This document discusses the Basic Local Alignment Search Tool (BLAST), which allows users to compare a query DNA or protein sequence against sequence databases to find regions of local similarity. BLAST breaks the query into short words that are then searched for in database sequences. When words are found in common, BLAST extends the alignment in both directions to find higher-scoring matches. BLAST outputs include a graphical display of alignments, a hit list ranking matches by similarity score, and detailed alignments. BLAST has many applications, such as identifying species, establishing evolutionary relationships, DNA mapping, and locating protein domains.
European molecular biology laboratory (EMBL)
European Molecular Biology Laboratory (EMBL) is one of the biggest database related to bioinformatics research work.
Molecular modeling database
The Molecular Modeling Database (MMDB) is a database hosted by the National Center for Biotechnology Information that contains over 28,000 experimentally determined 3D structures of biomolecules including proteins and nucleic acids derived from the Protein Data Bank, excluding theoretical models. It facilitates computation and links structures to other data types. Each record cross-references its source PDB file. The database contains molecular structures, biological activity data, experimental data, chemical properties, and annotations to aid researchers. Examples of widely used molecular modeling databases discussed are the Protein Data Bank, PubChem, and RCSB Ligand Explorer.
MULTIPLE SEQUENCE ALIGNMENT
This document discusses multiple sequence alignment techniques. It begins with definitions of key terms like homology, similarity, and conservation. It then describes pairwise alignment and its applications. The rest of the document focuses on multiple sequence alignment methods like progressive alignment, iterative refinement, tree alignment, star alignment, and using genetic algorithms. It provides examples and explanations of popular multiple sequence alignment tools like Clustal W and T-Coffee.
Ab Initio Protein Structure Prediction
Ab initio protein structure prediction uses computational methods to predict a protein's 3D structure from its amino acid sequence. It relies on conformational searching to generate structure decoys and selecting native-like models. The key factors for success are an accurate energy function, efficient search methods like molecular dynamics or genetic algorithms, and effective selection of models close to the native structure. Model selection approaches include energy evaluations, compatibility scores, clustering of similar decoys, and identifying the lowest energy conformations.
Uni prot presentation
UniProt is a comprehensive, freely accessible database that is a central repository for protein data. It is produced through collaboration between the European Bioinformatics Institute, Swiss Institute of Bioinformatics, and Protein Information Resource. UniProt contains protein sequences, functional information, evolutionary data, and details about biological processes, post-translational modifications, interactions, and subcellular locations to characterize proteins.
Biological databases
This document summarizes different types of biological data and biological databases. It discusses primary databases like GenBank, EMBL and DDBJ that contain raw nucleotide sequence data. Secondary databases like KEGG and Pfam analyze and annotate primary database content. Composite databases like NCBI aggregate data from multiple primary sources. Protein databases discussed include Swiss-Prot, TrEMBL, PDB, and Pfam. Structural databases such as SCOP, CATH and PDB organize protein structures.
Kegg databse
Rashi Srivastava presented on the KEGG database in biotechnology. KEGG is a database that contains genomic, chemical, and systems information to understand biological functions from the molecular level up. It includes pathways, genes, compounds, diseases, drugs, and organisms. KEGG can be searched through its flat file format using DBGET or through its relational database format for more complex queries. It also contains the KEGG MEDICUS search tool and direct SQL searches of its relational database.
Protein protein interaction
Protein-protein interactions are important for many biological processes. There are various types of interactions depending on their composition and duration. Methods to study interactions include yeast two-hybrid, co-immunoprecipitation, affinity chromatography, and chromatin immunoprecipitation. Databases such as IntAct and MINT provide repositories for protein interaction data.
Multiple sequence alignment
Multiple sequence alignment (MSA) aligns three or more biological sequences, like proteins or nucleic acids, to infer homology and evolutionary relationships. There are three main methods - dynamic programming computes an optimal alignment but has high runtime; progressive alignment first does pairwise alignments and adds sequences; iterative alignment successively improves approximations without pairwise alignments. Popular tools for MSA include Clustal W, MAFFT, MUSCLE, and T-Coffee. MSA helps detect similarities, conserved motifs, and structural homologies between sequences.
Rasmol
Rasmol and Swiss-PDB viewer are molecular visualization tools that allow users to view and analyze protein structures. Rasmol can display molecules in various representations like wireframe, cylinders, or ribbons. It supports common file formats like PDB and can rotate, zoom, and translate structures. Swiss-PDB viewer is tightly integrated with homology modeling and allows users to build models, compare structures, and view electron density maps. It utilizes template structures from the PDB to generate models and assess their quality. Both tools provide publication-quality images and interactive visualization of biomolecular structures.
Protein database
This document provides an overview of several important protein databases:
- SWISS-PROT is an annotated protein sequence database that is maintained collaboratively and contains over 1.29 million entries. TrEMBL is a computer-annotated supplement to SWISS-PROT containing sequences not yet in SWISS-PROT.
- Structural databases like PDB, SCOP, and CATH provide protein structure information. PDB is an international repository for macromolecular structures. SCOP and CATH classify protein domains based on structural similarities and evolutionary relationships.
- Other databases mentioned include InterPro, GOA, Proteome Analysis, and GenBank, which provide functional annotation, gene ontology assignments, proteome analysis
Gene prediction methods vijay
Automated sequencing of genomes require automated gene assignment
Includes detection of open reading frames (ORFs)
Identification of the introns and exons
Gene prediction a very difficult problem in pattern recognition
Coding regions generally do not have conserved sequences
Much progress made with prokaryotic gene prediction
Eukaryotic genes more difficult to predict correctly
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This document discusses using computational tools like Interactive Chromatin Modeling (ICM) and the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to model chromatin structure and behavior. ICM allows generating chromatin templates based on DNA sequence and known nucleosome positioning. LAMMPS is then used to simulate the chromatin structures generated by ICM and minimize collisions between molecules. The goal is to better understand chromatin packing and dynamics through computational modeling and analysis.
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Prediction of the three dimensional structure of a given protein sequence i.e. target protein from the amino acid sequence of a homologous (template) protein for which an X-ray or NMR structure is available based on an alignment to one or more known protein structures
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Homology modeling uses the amino acid sequence of a target protein and the 3D structure of a related template protein to generate a 3D model of the target. It involves aligning the target sequence to the template sequence, building the backbone of the target based on the template structure, modeling loops and side chains, optimizing the model structure, and validating the model. Homology modeling is most accurate when the sequence identity between the target and template is above 30%. It provides information about conserved regions and residues but is limited in modeling insertions, deletions, and side chains.
homology modellign lecture .pdf
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Pteridophytes
1. Selaginella is a heterosporous plant that produces megaspores and microspores. The spores develop into male and female gametophytes within their spore walls.
2. Microspores develop into male gametophytes containing antherozoids for fertilization. Megaspores develop into female gametophytes containing archegonia.
3. Fertilization occurs when antherozoids enter the archegonia through openings in the neck canal cells. This leads to the development of a diploid sporophyte within the megaspore.
Temperate forests and tropical rain forests
The word forest is derived from Latin ‘Foris’ meaning outside, the reference being to village boundary fence, and must have included all uncultivated and uninhabitated land.
Today a forest is any land managed for the diverse purposes of forestry whether covered with trees, shrubs, climbers, etc.
The forest biomes include a complex assemblage of different kinds of biotic communities.
Optimum conditions of temperature and ground moisture responsible for the growth of trees contribute greatly to the establishment of forest communities.
In addition, 50 mm rainfall is a pre-requisite for the trees.
The nature of soil, wind and air currents determines the distribution (abundance or sparseness) of forest vegetation.
The temperate forest biomes are characterized by a moderate climate and broad-leaved deciduous trees, which shed their
leaves in fall, are bare over winter and grow new foliage in the spring.
Seasonal variation in cambial activity
The timing of cambial reactivation plays an important role in determination of the amount and quality of wood and the environmental adaptavity of trees.
Environmental factors, such as temperatures, influence the growth and development of trees.
Temperatures from late winter to early spring affect the physiological process that are involved in the initiation of cambial cell division and xylem differentiation in trees.
Cumulative elevated temperatures from late winter to early spring result in earlier initiation of cambial reactivation and xylem differentiation in tree stems and an extended growth period.
However, earlier cambial reactivation increases the risk for frost damage because the cold tolerance of cambium decreases after cambial reactivation.
A better understanding of the mechanisms that regulate wood formation in trees and the influence of environmental conditions on such mechanisms should help in efforts to improve and enhance the exploitation of wood for commercial applications and to prepare for climatic change.
Wood is the product of vascular cambium, and the formation of wood depends on the cambial activity of trees.
In temperate and cool zones, the vascular cambium of the stems of trees undergoes seasonal cycles of activity and dormancy, which are collectively known as annual periodicity.
This periodicity plays an important role in the formation of wood and reflects the environmental adaptivity of trees, for example their tolerance to cold in winter in cool and temperate zones.
The quantity and quality of wood depend on the division of cambial cells and the differentiation of cambial derivatives.
Cambial activity in trees is regulated by both internal factors, such as plant hormones, and environmental factors, such as, temperature, rainfall and photoperiod.
Temperature provides the appropriate physical conditions for the growth and development of trees in temperate and cool climates.
Timing of cambial reactivation is controlled by temperature, which influences both the quantity and quality of wood.
During the period from late winter to early spring, new cell plates are formed in the cambium and this springtime phenomenon is referred to as cambial reactivation.
Species concept
To determine the variation and the limitation between species, many concepts have been proposed.
When a taxonomist study a particular taxa, he/she must adopted a species concept and provide a species limitation to define this taxa.
Plant kingdom as other living kingdoms has a hierarchy structure ends mostly with species rank.
Species are one of the basic units to compare in almost all fields of biology.
A species is defined as the largest group of organisms in which two individuals are capable of reproducing fertile offspring, typically using sexual reproduction.
Definition of a species as a group of interbreeding individuals cannot be easily applied to organisms that reproduce only or mainly asexually.
If two lineages of oak look quite different, but occasionally form hybrids with each other, should we count them as different species?
Idea of a species is something that we humans invented for our own convenience.
‘‘No matter what variations occur in the individuals or the species, if they spring from the seed of one and the same plant, they are accidental variations and not such as distinguish a species permanently; one species never springs from the seed of another nor vice versa” - JOHN RAY.
Used a sexual system ‘‘natural system” for defining species - LINNAEUS.
‘‘A species is a collection of all the individuals which resemble each other more than they resemble anything else, which can by natural fecundation produce fertile individuals, and which reproduce themselves by generation, in such a manner that we may from analogy suppose them all to have sprung from one single individual” - DE CANDOLLE.
Bryophytes as ecological indicators
Bryophytes are a diverse group of land plants.
Have large ecological impact.
23,000 described species world wide.
Largest group of land plants except for the flowering plants.
Integral part of natural environment of forest ecosystems.
Bryophytes are of small size.
Some of them attain a height up to half meter or a little more.
Store large amount of water, nutrients and carbon in their biomass.
In peatlands, bryophytes function as carbon sinks, which is a matter of great concern when considered with the rise of global carbon dioxide level.
Ability to remain alive for a long period without water even
under high temperature, and then resume photosynthesis within seconds after being moistened by rain or dew.
Most bryophytes are ectohydric, i.e., ability to absorb water, inorganic nutrients and mineral elements directly from the atmosphere rather than the soil and substratum.
Bryophytes possess short-lived sporophytic and dominant gametophytic phase.
Gene targeting and sequence tags
To modifying the structure of a specific gene.
Gene targeting vector introduced into the cell.
Vector modifies the normal chromosomal gene through homologous recombination.
Useful in treating some human genetic disorders – Hemophilia, Duchenne Muscular Dystrophy.
Treating human diseases by genetic approaches – Gene Therapy.
Gene Therapy – Replacing the defective gene by normal copy of the gene.
Expressed sequence tag/EST is a short partial sequence, typically 200-400 bp long, of a complimentary DNA/Cdna.
EST is a short sub-sequence of a cDNA sequence.
Used to identify gene transcripts, and are instrumental in gene discovery and in gene-sequence determination.
Approximately 74.2 million ESTs are available in public databases.
EST results from one-short sequencing of a cloned cDNA.
Low-quality fragments.
Length is approximately 500 to 800 nucleotides.
Cell signaling
Cells of multicellular organisms detect and respond to countless internal and extracellular signals that control their growth, division, and differentiation during development, as well as their behavior in adult tissues.
At the heart of all these communication systems are regulatory proteins that produce chemical signals, which are sent from one place to another in the body or within a cell, usually being processed along the way and integrated with other signals to provide clear and effective communication.
Study of cell signaling has traditionally focused on the mechanisms by which eukaryotic cells communicate with each other using extracellular signal molecules such as hormones and growth factors.
Many bacteria, respond to chemical signals that are secreted by their neighbors and accumulate at higher population density. This process, called quorum sensing, allows bacteria to coordinate their behavior, including their motility, antibiotic production, spore formation, and sexual conjugation.
Communication between cells in multicellular organisms is mediated mainly by extracellular signal molecules.
Most cells in multicellular organisms both emit and receive signals. Reception of the signals depends on receptor proteins, usually (but not always) at the cell surface, which bind the signal molecule. The binding activates the receptor, which in turn activates one or more intracellular signaling pathways or systems.
These systems depend on intracellular signaling proteins, which process the signal inside the receiving cell and distribute it to the appropriate intracellular targets.
The targets that lie at the end of signaling pathways are generally called effector proteins, which are altered in some way by the incoming signal and implement the appropriate change in cell behavior.
Depending on the signal and the type and state of the receiving cell, these effectors can be transcription regulators, ion channels, components of a metabolic pathway, or parts of the cytoskeleton.
Chlorophyta
Chlorophyta are a division of green algae that contain about 20,000 species. They are eukaryotic organisms with membrane-bound organelles like chloroplasts containing chlorophyll. Their thalli range from unicellular to multicellular filamentous forms. Reproduction can occur asexually through zoospores or sexually from isogamy to oogamy. They exhibit a variety of life cycles including haplontic and diplohaplontic patterns with alternation of generations. Chlorophyta are an important group of photosynthetic organisms and include many common pond algae.
Immobilization of enzymes
Enzyme immobilization is defined as confining the enzyme molecules to a distinct phase from the one in which the substrates and the products are present.
It is achieved by fixing the enzyme molecules to or within some suitable material.
Impact of biotechnology
Most developments in biotechnology originated for their potential applications in health care.
Contributions of biotechnology are more frequent, more notable and more rewarding in health sector.
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Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
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dtubbenhauer@gmail.com
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Molecular visualization
- 2. INTRODUCTION Looking at molecular models in order to explore and understand them. Does not necessarily involve molecular modeling (changing the existing model). Macromolecules – Protein, DNA, RNA, or their complexes. 3-D view of different molecules on the computer.
- 3. REPRESENTATIONS OF MOLECULAR MODELS ATOMIC REPRESENTATION It includes ball and stick, stick (wireframe), and spacefilling. These representations show positions of atoms and covalent bonds.
- 4. SLABBING A usefull way to see atomic details of a small part of a large macromolecular model is to centre the moiety of interest, and then cut away front and back portions of the molecules. It is usefull to see buried structures and their environments, such as the hydrophobic core of a protein domain. It can be done using FirstGlance in Jmol.
- 5. SIMPLIFIED SCHEMATIC REPRESENTATIONS BACKBONES Simplified representations of the polypeptide backbone or main chain, are very helpful in understanding structure when it comes to large molecules such as Proteins, DNA, RNA, and their complexes. Using FirstGlance in Jmol.
- 6. DISULFIDE BONDS FirstGlance in Jmol highlights disulfide bonds in one click, and has several options for rendinering and coloring them.
- 7. COLOUR SCHEMES FOR MACROMOLECULES A set of standard color schemes for macromolecules, called DRuMS, was released in 2000. Colors for chemical elements.
- 8. STRUCTURAL ANALYSIS Molecular function. Prediction of function. Experimental design to test predictions.
- 9. TYPES OF MOLECULAR VISUALIZATION WIRE FRAME MODEL. BALL AND STICK MODEL. RIBBON SHAPED MODEL. SPACE FILLING. SIMPLE HARMONIC MODEL. BACKBONE. SURFACE.
- 10. WIRE FRAME MODEL Skeletal form of molecules – represent as wires. Network of wire. Line represents the bonds. Shows individual bonds and corresponding angles.
- 11. RIBBON SHAPED MODEL Spherical or cylindrical ribbons. Display the folding and structure of proteins.
- 12. BALL AND STICK MODEL Ball represents the atoms. Stick represents the bonds. Shows atomic positions and bonds and volume.
- 13. SIMPLE HARMONIC MODEL Only represents grooves and projections in the molecules.
- 14. SPACE FILLING Spheres represents the electro cloud around nuclei of atoms. Relative size of atoms and groups show up clearly. Merged spheres represents the sharing of electrons.
- 15. RasMol Most frequently available tool. Derived from Raster and molecules. Molecular graphics programe. For visualizing proteins, nucleic acid and small molecules for which 3-D structures is available. In order to display molecules, RasMol requires atomic coordinate file that specifies the position of every atom in the molecule through its 3-D Cartesian coordinates. RasMol accept this coordinate file variety of formats including Protein Data Bank format.
- 16. It provides user a choice of colour schemes and molecular representation. Additional features including test labelling for slected atoms, different colour schemes of different parts of the molecule, zoom, rotation etc.
- 17. REFERENCE Jin Xiong (2007) Essential Bioinformatics, Cambridge University, PressIndia, Pvt LTD. Wikipedia - Molecular Visualization, Bioinformatics.
- 18. THANK YOU