This document discusses methods for constructing phylogenetic trees including distance-based and character-based approaches. Distance-based methods include UPGMA, Neighbor-Joining (NJ), and Fitch-Margoliash (FM) which use genetic distances between sequences. Character-based methods include Maximum Parsimony (MP) which finds the tree requiring the fewest evolutionary changes, and Maximum Likelihood (ML) which calculates the probability of the observed sequence changes. NJ is the fastest method while ML is the slowest but uses all available sequence data. The appropriate method depends on factors like number of sequences and computational requirements.
In this presentation, I talk about the various tools for the submission of DNA or RNA sequences into various sequence databases. The sequence submission tools talked about in this presentation are BankIt, Sequin and Webin.
In this presentation, I talk about the various tools for the submission of DNA or RNA sequences into various sequence databases. The sequence submission tools talked about in this presentation are BankIt, Sequin and Webin.
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.
Secondary Structure Prediction of proteins Vijay Hemmadi
Secondary structure prediction has been around for almost a quarter of a century. The early methods suffered from a lack of data. Predictions were performed on single sequences rather than families of homologous sequences, and there were relatively few known 3D structures from which to derive parameters. Probably the most famous early methods are those of Chou & Fasman, Garnier, Osguthorbe & Robson (GOR) and Lim. Although the authors originally claimed quite high accuracies (70-80 %), under careful examination, the methods were shown to be only between 56 and 60% accurate (see Kabsch & Sander, 1984 given below). An early problem in secondary structure prediction had been the inclusion of structures used to derive parameters in the set of structures used to assess the accuracy of the method.
Some good references on the subject:
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.
It is possible to reconstruct the evolutionary relationships (ancestral relationships) among the genes and organisms. This involves creating a branching structure, termed phylogeny or tree that determines the relationships between sequences. Phylogenetic analysis of a family of related nucleic acid or protein sequences is a determination of how the family might have been derived during evolution. Placing the sequences as outer branches on a tree represents the evolutionary relationships. Two sequences that are much alike will be located as neighbouring outside branches and would be joined to a common branch beneath them.
Phylogenetic tree is a 2- dimensional graph showing the evolutionary relationship among the organisms.
The tree is composed of nodes [ where branches bifurcate] representing the taxa and branches representing the relationships among the taxa.
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.
Secondary Structure Prediction of proteins Vijay Hemmadi
Secondary structure prediction has been around for almost a quarter of a century. The early methods suffered from a lack of data. Predictions were performed on single sequences rather than families of homologous sequences, and there were relatively few known 3D structures from which to derive parameters. Probably the most famous early methods are those of Chou & Fasman, Garnier, Osguthorbe & Robson (GOR) and Lim. Although the authors originally claimed quite high accuracies (70-80 %), under careful examination, the methods were shown to be only between 56 and 60% accurate (see Kabsch & Sander, 1984 given below). An early problem in secondary structure prediction had been the inclusion of structures used to derive parameters in the set of structures used to assess the accuracy of the method.
Some good references on the subject:
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.
It is possible to reconstruct the evolutionary relationships (ancestral relationships) among the genes and organisms. This involves creating a branching structure, termed phylogeny or tree that determines the relationships between sequences. Phylogenetic analysis of a family of related nucleic acid or protein sequences is a determination of how the family might have been derived during evolution. Placing the sequences as outer branches on a tree represents the evolutionary relationships. Two sequences that are much alike will be located as neighbouring outside branches and would be joined to a common branch beneath them.
Phylogenetic tree is a 2- dimensional graph showing the evolutionary relationship among the organisms.
The tree is composed of nodes [ where branches bifurcate] representing the taxa and branches representing the relationships among the taxa.
introduction to upgma software , its history and origination, basic mening of upgma, the upgma algorithm, steps to perform upgma, and its diagramatic representation of the process along with an example, its application, advantages along with the disadvantages, and its uses.
A phylogenetic tree is a model about the evolutionary relationship between operational taxonomic units(OTUs) based on homologous character.
Dandrogram: general term for a branching diagram
Cladogram: branching diagram without branch length estimates
Phylogram or phylogenetic tree: branching diagram with branch length estimates
A tree is composed of nodes and branches & one bracnch connects any two adjacent nodes. Nodes represent the taxonomic units.
E.G. Two very similar sequence will be neighbours on the outer branches and will be connected by a common internal branch.
Course slides for computational phyloinformatics, an annual course organized by NESCent in collaboration with hosting organizations across the world. I am the teacher of the Perl section of the course, these are the slides I presented in 2010 at BGI, Shenzhen, PRC.
International Journal of Computer Science, Engineering and Information Techno...IJCSEIT Journal
In the field of proteomics because of more data is added, the computational methods need to be more
efficient. The part of molecular sequences is functionally more important to the molecule which is more
resistant to change. To ensure the reliability of sequence alignment, comparative approaches are used. The
problem of multiple sequence alignment is a proposition of evolutionary history. For each column in the
alignment, the explicit homologous correspondence of each individual sequence position is established. The
different pair-wise sequence alignment methods are elaborated in the present work. But these methods are
only used for aligning the limited number of sequences having small sequence length. For aligning
sequences based on the local alignment with consensus sequences, a new method is introduced. From NCBI
databank triticum wheat varieties are loaded. Phylogenetic trees are constructed for divided parts of
dataset. A single new tree is constructed from previous generated trees using advanced pruning technique.
Then, the closely related sequences are extracted by applying threshold conditions and by using shift
operations in the both directions optimal sequence alignment is obtained.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A COMPARATIVE ANALYSIS OF PROGRESSIVE MULTIPLE SEQUENCE ALIGNMENT APPROACHES ...ijcseit
Multiple sequence alignment is increasingly important to bioinformatics, with several applications rangingfrom phylogenetic analyses to domain identification. There are several ways to perform multiple sequencealignment, an important way of which is the progressive alignment approach studied in this work.Progressive alignment involves three steps: find the distance between each pair of sequences; construct a guide tree based on the distance matrix; finally based on the guide tree align sequences using the concept of aligned profiles. Our contribution is in comparing two main methods of guide tree construction in terms of both efficiency and accuracy of the overall alignment: UPGMA and Neighbor Join methods. Our experimental results indicate that the Neighbor Join method is both more efficient in terms of performance and more accurate in terms of overall cost minimization.
A COMPARATIVE ANALYSIS OF PROGRESSIVE MULTIPLE SEQUENCE ALIGNMENT APPROACHES ijcseit
Multiple sequence alignment is increasingly important to bioinformatics, with several applications ranging from phylogenetic analyses to domain identification. There are several ways to perform multiple sequence alignment, an important way of which is the progressive alignment approach studied in this work.Progressive alignment involves three steps: find the distance between each pair of sequences; construct a
guide tree based on the distance matrix; finally based on the guide tree align sequences using the concept of aligned profiles. Our contribution is in comparing two main methods of guide tree construction in terms of both efficiency and accuracy of the overall alignment: UPGMA and Neighbor Join methods. Our experimental results indicate that the Neighbor Join method is both more efficient in terms of performance
and more accurate in terms of overall cost minimization.
A COMPARATIVE ANALYSIS OF PROGRESSIVE MULTIPLE SEQUENCE ALIGNMENT APPROACHES ...ijcseit
Multiple sequence alignment is increasingly important to bioinformatics, with several applications ranging
from phylogenetic analyses to domain identification. There are several ways to perform multiple sequence
alignment, an important way of which is the progressive alignment approach studied in this work.
Progressive alignment involves three steps: find the distance between each pair of sequences; construct a
guide tree based on the distance matrix; finally based on the guide tree align sequences using the concept
of aligned profiles. Our contribution is in comparing two main methods of guide tree construction in terms
of both efficiency and accuracy of the overall alignment: UPGMA and Neighbor Join methods. Our
experimental results indicate that the Neighbor Join method is both more efficient in terms of performance
and more accurate in terms of overall cost minimization.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
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.
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.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
2. Phylogenetic tree:
Phylogenetic tree is other
wise known as phylogeny is a diagram
that represents the lines of evolutionary
descent of different species, organisms or
genes from a common ancestor. The tree
contain a nodes , branches , clade.
3.
4. Tree building is a method to Phylogenetic
analysis there are two types
Distance
based
method
Character
based
method
5. Distance based method:
All possible pairs of sequences are aligned to
determine which pairs are the most similar or closely related.
These alignments provide a measure of the genetic distance
between the sequences. These distance measurements are then
used to predict the evolutionary relationship.
These methods are:
UPGMA.
NJ.
FM.
MINIMUM EVOULATION .
7. Distance based method:
UPGMA(Unweighted pair group method
with arithmetic mean) this method is a simplest method of
tree construction it is a cluster analysis derived from the
clustering algorithms proposed by skoal and sneath (1973)
it was originally developed for constructing taxonomic
phenograms and it can also used to construct a Phylogenetic
trees.
UPGMA employs a sequential clustering algorithm
.
We first identify from among all the OTU s the 2
OTUs that are most similar to each other and then treat these
a new single OTU.
This method is least accurate but is widely used.
8. STEPS:
This method begins with the construction of a distance
matrix.(dij)
The two taxa that have the smallest distances are clustered
together (I and j are taxa)and form a OTU.
The branch lengths for the I and J taxa are taken to be half
of the distance between them(dij/2)
I and J is a average distance and form a new taxa k.
These all of them are clustered it forms a dik+djk/2.
The average length is taken to be the average distance
between OTU.
9.
10. NEIGHBOR JOINIG METHOD(NJ):
It is a simplest distance method. It
begins by choosing the two most closely
related sequences and then adding the next
most distant sequence as third branch of tree.
This method is developed in 1987 by saitou
and nei. This method produces a unrooted
trees.
11. Advantage:
this method is a fast and the large datasets
for bootstrap analysis.
This method permits correction for multiple
substitutions.
It can use empirical substitutions scoring
methods.
Disadvantage:
it can perform only a single tree.
It does not consider intermediate ancestors.
In this method sequence information is
reduced.
12.
13. FITCH-MARGOLIASH METHOD:
it is a common pair-wise clustering
algorithm FM method. This method
developed by FITCH-MARGOLIASH(1967)
he showed that different sets of internal
branch lengths could be obtained by
considering alternate trees which moved one
or more branches to different parts of the tree.
14.
15. Advantage:
It tests more than one tree.
Fastly method.
It can use empirical substitution
scoring methods.
Disadvantage:
Requires long time compare to NJ
method.
It does not consider intermediate
ancestors.
Long evolutionary distances will be
underestimated.
16. MINIMUM EVOLUTION:
First aided by Kidd & sgaramella-
zonta in 1971. the minimum evolution tree is
the tree which minimizes L.
It give an unrooted metric tree for n
sequences there are (2n-3)branches, each with
length ei L is for length.
This method is similar to parsimony
method.
17.
18. Advantages:
easy to perform.
Quick calculation.
Disadvantage:
The sequence are not considered so the
information will be loss.
Not applicable to distantly divergent
sequences.
19. CHARACTER METHOD:
Maximum parsimony method(MP)
In MP method a multiple sequence alignment is
produced in order to predict which sequence positions are
likely to correspond.. These position will appear in vertical
column in MSA.
For each aligned position, Phylogenetic trees that
requires the smallest number of evolutionary changes to
produce the observed sequence changes are identified.
Finally those trees which produce the smallest
number of changes overall for all sequences are identified.
This method attempts to reconstruct mutational events
leading to the currently observed sequences.
20. The point of maximum parsimony is
that although sequences could be placed at
any position on the tree, the number of steps
required to interconvert one sequence to
another changes at each time branches are
moved.
Thus the parsimonious tree is the tree
whose topology requires the fewest total
mutations.
21. Advantages:
Reconstruct ancestral nodes.
It can be better performance than
distance based method.
It provides numerous “most
parsimonious trees”
Disadvantage:
branch lengths can not be determined
only topology.
Slower than matrix methods.
Sensitive to order in which sequences
are added to tree.
22.
23. MAXIMUM LIKELIHOOD:
ML methods depends upon the first
obtaining a reliable sequence alignment and then
examining the changes in each column in the
alignment.
The likelihood its finding the actual
sequence changes at each columns in the aligned
sequence is calculated.
The probabilities for each aligned position
are then multiplied to provide likelihood for each
tree.
The tree that provide the maximum
likelihood value is the most probable tree.
24. This method introduced by Edwards and cavalli-
sforza(1964)for Phylogenetic analysis.
The main feature:
substitution model is chosen for the sequence
data.
Likelihood of observing the data in
substitution model is obtained for each topology
evaluated.
Topology that gives the highest likelihood is
chosen as the best tree.
25. The ML to phylogeny is implemented in DNAML
and PHYLIP package and in a modified version of DNAML
called fastDNAml(optimizing the tree by ML at each step)
The ML method of inference is available for both protein and
nucleic acid.
The following programs are
1.DNAML (only DNA data in the PHYLIP package)
2.Fast DNAML (only DNA data, a faster algorithm
to applied to DNAML)
3.ProtML(both DNA and protein data)
4.Puzzle(both DNA and protein data). This programs
is much faster than PROTML
26. Advantages:
uses all the sequence information.
Reconstruct ancestral nodes.
Generate branch lengths.
It has been perform better than
distance methods.
Disadvantage:
it is very slow.
It needs a long time to construct a tree.
27.
28. NJ MP ML
Employs distance
between pairs of
sequence.
It employs a subset of
the alignment position of
the sequences.
It employs all the data
Minimize the distances
between the closed
neighbor.
Minimizes the total
distance
It maximize the
likelihood of the given
certain values for the
parameters.
Very fast slow Very slow
A good choice to
construct on initial tree
or to choose between
many candidates trees.
A good choice for less
than 30 sequences and
when homoplasy is rare.
A good choice for small
data sets and for
validating the trees
constructed by other
methods