Bio Informatics

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“Bio Informatics frequently Asked Questions by expert members with experience in Bio Informatics. So get preparation for the Bio Informatics job interview”

20 Bio Informatics Questions And Answers

1⟩ What is e value?

Expectation value. lower the e value more significant is the

match. it gives the statistical significance of a match to

signify whether a match has taken by chance alone or not.


2⟩ Can isolation of DNA done with perfection? how?

For isolating the DNA from specific source,we first know the

behavior of cell morphology because cell wall playing

important role in protecting the inner content. By using

various chemicals and there composition helps in isolating

the DNA from source cell.


7⟩ What is the meaning of science?

Science is the term given to the powerfull branch which

forces a living thing to struggle and win the obstacles

existing in the mother earth. A dragging power which

motivates the life.


8⟩ Which of the following sequences contains the pattern [AG]-x(4)-G-K-[ST] from the PROSITE database?seq. A VAGWGKST seq B GVLKRGKS seq. C AGVLKGRT seq. D AGVGKSTP?


[AG]-x (4)-G-K-[ST]

decodin the pattern:

A or G in the first position,(note both sequence C and D

start with the same)

X any amino acid follows the next four positions (2-5)

G in the sixth position (note seq C alone satify)

k in the seventh position

S or T in the eigth position (note seq C alone satify)


9⟩ What is the main idea of maximum parsimony in phylogenetic tree construction? What are the drawbacks?

The Maximum Parsimony (MP) problem aims at reconstructing a

phylogenetic tree from DNA sequences while minimizing the

number of genetic transformations. To solve this NP-

complete problem, heuristic methods have been developed,

often based on local search. In this paper, we focus on the

influence of the neighborhood relations


11⟩ Explain Homology modelling?

if the crystal structure of any protein is unavailable,

then one can use the tools of homology modelling to

determine the structure. the logic is that a similar

structure arises becuse of a similar sequence of amino

acids. for homology modelling to be accurate an identity

match of 70% is desirable.basically, one does a FASTA

search of A.A sequences in the PDB database (A.A sequences

whose structures are known), does a CLUSTAL alignment to

check for conserved residues. then the structure of the

unknown A.A sequence is built up on the basis of the

structure of the best matches in FASTA and CLUSTAL by

programs like LLOOP and HHPRED. this structure can be

visualized in programs like DEEPVIEW,Protein Explorer



12⟩ How to run DOCK 6 using cygwin?

1.install the needed package such as bison, perl etc.....

2.Configure the gnu file using ./configure gnu....

3.Download the accessary programs, such as dms, sphgen,


4.Prepare the structure and form the spheres and then built

the grid for the ligand.....

5.Dock the molecule, by selecting the rigid dcking or

flexible docking...

6.Give the input file for the selected docking and obtain

the output.....



i like this field because advanced technique of

biology,combined of biotechnology and information

technology,mainly use for drug designing and research, if

anybody research in biological science use for



16⟩ What is the difference between present and oldest drug discovery methods?

in oldest drug discovery we use to do hit and trial method for drug discovering we use to make a formula manually and then to design a drug but now that work has been reduce by new softwares and tools now we can avoid this hit and trial method now we can design a drug and can create an hypothesis about that drug and can also predict its efficiency for targetting to the receptor


18⟩ Derive e-value?

Expect value. The E-value is a parameter that describes the

number of hits one can “expect” to see by chance when

searching a database of a particular size. It decreases

exponentially with the score (S) that is assigned to a

match between two sequences. Essentially, the E-value

describes the random background noise that exists for

matches between sequences. For example, an E-value of 1

assigned to a hit can be interpreted as meaning that in a

database of the current size, one might expect to see one

match with a similar score simply by chance. This means

that the lower the E-value, or the closer it is to “0”, the

higher is the “significance” of the match. However, it is

important to note that searches with short sequences can be

virtually identical and have relatively high E-value. This

is because the calculation of the E-value also takes into

account the length of the query sequence. This is because

shorter sequences have a high probability of occurring in

the database purely by chance


19⟩ What are the main approaches of predicting protein interactions using genomic context analysis?

We have developed an approach using Bayesian networks to

predict protein-protein interactions genome-wide in yeast.

Our method naturally weights and combines into reliable

predictions genomic features only weakly associated with

interaction (e.g., messenger RNAcoexpression,

coessentiality, and colocalization). In addition to de novo

predictions, it can integrate often noisy, experimental

interaction data sets. We observe that at given levels of

sensitivity, our predictions are more accurate than the

existing high-throughput experimental data sets


20⟩ How you calculate sensitivity and selectivity of Blast?

Suppose the Blast search returned 100 hits. Of these, 17

were false positives and we knew that there were 165

sequences in

the database which should have returned a hit with our


To calculate the sensitivity and selectivity, we must

determine the number of true positives (ntp), the number of


positives (nfp) and the number of false negatives (nfn). We

are told that the number of false positives was 17, hence


number true positives must have been 100-17 = 83, as there

were 100 hits. Therefore we know that the search algorithm


83 of the 165 sequences it should have found, hence the

number of false negatives was 165-83 = 82. So, we know that

ntp = 83,

nfp = 17 and nfn=82. Using the equations in the notes, we

can calculate:

Sensitivity = ntp/(ntp+nfn) = 83/(83+82) = 83/165 = 0.50 (2


Selectivity = ntp/(ntp+nfp) = 83/(83+17) = 83/100 = 0.83