Bioinformatics:Multiple sequence alignment different formats:

Bioinformatics:Multiple sequence alignment different formats:

People sometimes find it confusing when it comes to different multiple sequence alignment formats (what to use with what???), that's because the variety of programs that handles multiple sequence alignments, sometimes you find a program that uses FASTA format and sometimes MSF (Multiple Sequence Format)...etc.

The reason why there are a lot of formats out there, is that every format had appeared by specialists in a specific field, for example specialists in phylogeny use Phylip format...etc

So before you use any format you have to ask yourself questions like: is this format supported by the program i'm running, is it easy for me to modify in it, is it widely accepted...etc.

Some of the most popular multiple sequence alignment formats:

1- FASTA: a text format that's widely accepted and its easy to read and modify.
2- MSF: (Multiple Sequence Format), the most popular, supported by most programs, easy to read and difficult to modify.
3- ALN: produced by ClustalW, easy to read and widely supported.
4- Phylip: text format, supported by most phylogenetic packages.

Any question, u're welcome.

Bioinformatics: video tutorial: Using PHYLIP to build phylogenetic trees

Bioinformatics: video tutorial: Using PHYLIP to build phylogenetic trees

As you know PHYLIP or (PHYlogeny Inference Package) is a set of programs that can construct phylogenetic trees.


To understand what phylogenetic trees can do for you you can read this post HERE.

In order to build phylogenetic trees you have to prepare a set of sequences in a multiple sequence alignment.

In this video tutorial i'm going to use one of the 3 methods in building phylogenetic trees, which is distance methods by using a program included in PHYLIP called protdist.

This video tutorial have 2 parts:

Part 1:



Part 2:



Any questions, comment

Bioinformatics: Different methods used to build phylogenetic trees

Bioinformatics: Different methods used to build phylogenetic trees

In Bioinformatics there are three major methods used in building phylogenetic trees, every one of these methods have its own weaknesses and strengths as the case with every bioinformatics program or method.

These methods are:

1- Distance methods: In this method the algorithm takes the data (sequences) and construct a distance matrix between each 2 sequences, after that the sequences are regrouped depending on their relative distance, the last step is to construct a tree that matches this data.

2- Parcimony methods: This method searches in all possible phylogenetic trees that needs the minimum number of substitutions of nucleic acids or amino acids (mutations), so the best tree is the one that have the minimum number of mutations.

3- Likelihood methods: This method means that the best estimate of a parameter is that giving the highest probability that the observed set of measurements will be obtained.

Bioinformaticians say that Likelihood methods are the most accurate and the best, because most researchers use them, but the problem is that they run very slow because of their long algorithms.

Parcimony methods have great results but they have probably the same negative side of Likelihood methods.

Distance methods or distance based trees are easy to set up, and you can apply them in most situations, but they aren't necessarily the most accurate.



How to prepare your sequences for a phylogenetic tree

What Phylogenetic Trees can do for you?



Any question comment.

Bioinformatics: How to prepare your sequences for a phylogenetic tree

Bioinformatics: How to prepare your sequences for a phylogenetic tree

In order to make a phylogenetic tree, we have to do a multiple sequence alignment first, because you can't make a good and accurate tree without an accurate multiple sequence alignment.

To learn haw to build a multiple sequence alignment, you can see this video tutorial HERE.

To build a multiple seqeunce alignment and then a phylogenetic tree, you have to prepare you sequences considering some factors:

1- Avoid using sequence fragments: you have to align the complete sequences not only fragments, and if you want to align fragments, you have to use fragments for all sequences that you want to align.

2- Avoid using a lot of sequences: large datasets or large number of sequences can make your phylogenetic tree not accurate, because most algorithms can't handle large datasets especially softwares that are used online, because it will take a lot of time and hurt your phylogenetic tree accuracy.

3- Avoid aligning Xenologs: because they are produced by lateral transfer by a virus or bacteria, and they can't make the original history of your gene, if you want more information about Xenologs you can read this post HERE.

4- Avoid recombinant sequences: because recombinant sequences are a result of two species (may be very distinct species), Phlogenetic trees builders can't handle the history of two distinct species in the same time.

5- Add a distant sequence to your alignment: it has to be similar but diverged long time ago, because it will work as the first common ancestor to you phylogenetic tree.

6- Don't depend on guide trees: On EBI server for example, when you make a multiple sequence alignment with ClustalW, a guide tree is included in the results, don't use this tree because its not a phylogenetic tree, it's a guide tree that ClustalW uses to assemble the multiple sequence alignment, if you use it in place of phylogenetic tree, it will give you false results.

Any question you're welcome.

Bioinformarics: different types of homologous genes

Bioinformarics: different types of homologous genes

The main purpose of phylogeny is to pick what we call Homologous genes and compare them to construct a phylogenetic tree of their history, according to their similarities.

Homologous genes are genes that derive from a common ancestor. To understand the homologous genes types and how exactly they derive, we have to know couple of things

* Speciation: is the phenomenon during which a common ancestor gives birth to two subgroups that slowly drift away from their common genetic makeup to become distinct species.

* Duplication: Means that within the same genome of the same species, the gene was duplicated, in this case, may be one of the genes remain the same with the same function, and the other may change.


Homologous genes have three types:

1- Orthologs: Orthologs are 2 genes that are separated by speciation, it means generally that 2 genes exist in 2 different species, but they were in the same common ancestor.

2- Paralogs: Paralogs are 2 genes separated by duplication, this means that the same gene in one genome was duplicated to 2 genes or more.

3- Xenologs: Xenologs result from Lateral Transfer between 2 species or organisms, a DNA transfer from species to another, like the transfer of a DNA sequence from a virus or bacteria to another species.


In bioinlformatics collecting these genes from Blast searches, and aligning them into a multiple sequence alignment is the main tool to construct a phylogenetic tree.

Any questions, you are welcome.

How studying rRNA can help us studying evolution in Bioinformatics

How studying rRNA can help us studying evolution in Bioinformatics

Many of you are asking, how scientists have made an approximate tree of life that have almost all discovered species, well this is the answer:

In Evolutionary Bioinformatics scientists have tried to find a gene that exists in all living organisms, well the very appropriate gene in this case will be the rRNA coding gene.

rRNA or ribosomal RNA is the central component of the ribosome, its where proteines are manufactured in all living organisms, it's the one that interacts with tRNA or Transfert RNA to produce a protein from amino acids and mRNA or messenger RNA.

So the main criteria to study evolution is finding a conserved gene that exists in all living organisms, so the main thing scientists do when they discover new bacterium for example is to sequence its rRNA to identify its taxonomic group and estimate rates of species divergence.

As rRNAs have played and are playing a major role in Evolutionary Bioinformatrics, scientists and researchers have made specialized databases like RDP and the European database that have thousands of rRNA sequences stored.

Any question, comment.

Bioinformatics:Phylogeny: What Phylogenetic Trees can do for you?

Bioinformatics:Phylogeny: What Phylogenetic Trees can do for you?

As you know the purpose of phylogeny is to construct a history of life to better understand it, the main ourpose of phylogeny is to groupe organisms according to their similarities.

Genes mutates over time and changes, we mean by that EVOLUTION, that's why there are a lot of species (Diversity) on earth, and that's when Phylogenetics become an indispensable science to Bioinformatics especially Phylogeny.

Phylogenetics is a science that is part of phylogeny and that relies on the comparison of many species genes to find out which species are more related to others and to construct a tree of these species.

To better understand Phylogenetic trees you can read this post HERE.
To learn how to use Bioinformatics tools of constructing phylogenetic trees (As PHYLIP) you can read this post HERE.

Phylogenetic Trees can do:

1- Determining the most relative organism to yours your studying.

2- Determining the function of a gene by looking at its relatives (Orthologous genes).

3- Determining genes family.

4- Finding out about the origin of the gene you're studying.

Bioinformatics: Main Applications Of Multiple sequence Alignment

Bioinformatics: Main Applications Of Multiple sequence Alignment

You can read an introductory post to Multiple Sequence Alignment HERE, to understand what is a Multiple Sequence Alignment.

Multiple Sequence Alignment is almost the most useful tool in Bioinlformatics, it helps almost in every application of Bioinformatics (predicting protein structure, predicting protein function, phylogenetic analysis...etc).

The main applications of Multiple Sequence Alignment are:

1- Structure Prediction: a Multiple Sequence Alignment can give you the almost perfect protein or RNA secondary structure, some times it helps even with the 3D structure.

2- Protein Family: a Multiple Sequence Alignment can help you to decide that your protein is a member of a known protein family or not.

3- Pattern Identification: By looking at conserved regions or sites, you can identify which region is responsible for a functional site.

4- Domain Identification: By looking at file provided by a Multiple Sequence Alignment, you can extract profiles to use them against databases.

5- DNA Regulatory Elements: You can use Multiple Sequence Alignments to locate DNA regulatory elements such as binding sites...etc.

6- Phylogenetic Analysis: By carefully picking related sequences you can reconstruct a tree using sequences that u have used in the Multiple Sequence Alignment (You can use the PHYLIP package and you can find a post about it here).

As Multiple Sequence Alignments are playing a major role in Bioinformatics, you can use it almost anywhere but as every thing on this earth, nothing is perfect or 100% accurate, so u have to choose your sequences very carefully to prevent meaningless results.

You can access the EBI ClustalW program from HERE, to do a Multiple Sequence Alignment.

Any comments you're welcome.

Bioinformatics: PHYLogeny Inference Package (PHYLIP)

Bioinformatics: PHYLogeny Inference Package (PHYLIP)

PHYLIP or the PHYlogeny Inference Package is a package that contains a lot of programs for infering Phylogenies or by simple words constructing Phylogenetic or Evolutionary Trees.

The Package contains a lot of useful programs and above all of that its free and you can get it from its website from HERE

The Programs contained in the PHYLIP Package can estimate Phylogenies from Protein sequences or Nucleic Acid sequences with different methods (parsimony, maximum likelihood...etc)

It was and still very helpful for Bioinformaticiens and Phylogeny scientists and students as it can provide a complete environment for Phylogeny .

You can read the documentation file from HERE.

Any questions you're welcome.

Bioinformatics: Phylogenetic Trees

Bioinformatics: Phylogenetic Trees

Genetical, mophological, Biochemical evidences are now showing that all organisms on earth are genetically related, so every scientist is searching for what's called "The Tree Of Life" that represents the Phylogeny of organisms.

What is Phylogeny?

Phylogeny is the history of organismal lineages as they change through time. It implies that different species arise from previous forms via descent, and that all organisms, from the smallest microbe to the largest plants and vertebrates, are connected by the passage of genes along the branches of the phylogenetic tree that links all of Life.



Phylogenetic tree:

The Phylogenetic tree or Evolutionary tree is a tree showing the evolutionary relationship between various species that are thought to have a common Ancestor.

Each node in the tree represents the most recent common ancestor of the descendants, the edge lengths in some trees correspond to estimated time. Each node is called a taxonomic unit. Internal nodes are generally called hypothetical taxonomic units (HTUs) as they cannot be directly observed.

In Bioinformatics, Softwares align sequences of species that are thought to have a common ancestor ( multiple sequence alignment) , and calculate the distance between organisms (by using the number of mutations...etc), in the end it displays a graphical view of the tree with nodes and their corresponding edge lengths.

Any comments you are welcome.