Theme images by Storman. Powered by Blogger.

Blog Archive

Recent in Sports

Home Ads



Random Posts

Search This Blog



Friday, 24 August 2018

Input Guarding in Biomedical Instrumentation

- No comments

Input Guarding in Biomedical Instrumentation

As we know, the physiological signals have very low amplitudes. In all cases, the common mode noise will affect the measurement accuracy. Due to the effect of common mode signals the bioelectric amplifiers cannot distinguish the artifact (noise signal) from the original signal. Also the stray leakage paths can increase the input currents and decrease the input resistance unless we use a guard at the inputs. A schematic representation of input guarding is shown in figure.

Input Guarding in Biomedical Instrumentation
So we use the method of input guarding. Actually the main aim of input guarding is to avoid the effect of common mode noise. Guarding is used to reduce parasitic leakage currents by isolating a sensitive amplifier input from large voltage gradients across the PC board. The guard is a conductive PC trace surrounding the input terminals or in physical terms it is a low impedance conductor that completely surrounds an input line or node. It is biased to a potential equal to the line's voltage. Common mode noise occurs because of the unbalance in potential at the inputs. So by placing the shield at the common mode signal potential, the common mode noise can be rejected. Also the guard ring connects to a low impedance point at the same potential as the inputs. The stray leakages are absorbed by the low impedance ring. The equal potential between ring and inputs prevents the input leakage currents. The exact technique for guarding depends on the amplifier’s mode of operation, i.e., whether the input is inverting or a non-inverting type.

Chopper Stabilized Amplifier Principle

- No comments

Chopper amplifiers are dc amplifiers. Some minute amplitude signals needs high gain amplification .But very high dc amplifier design can be complicated because they are very difficult to build up with low offset and I/fnoise. Also stability and bandwidth may not be up to the mark. For the lowest offset and drift performance chopper stabilized amplifiers may be the only solution. Offset voltages less than 5 ┬ÁV with extremely low offset drifts are available with chopper stabilized amplifiers.

So chopper amplifier is used to break up the input signal so that it can be processed as if it were an ac signal and then integrate back to the dc signal at the output. In this way extremely small input signals can be amplified. So DC chopper amplifier provides high accuracy and stability which is a key requirement in biomedical instrumentation field.

So in the case of chopper amplifiers, the signal is sampled to chop (convert) the signal at a frequency that will pass through the ac-amplifier. Many biomedical chopper amplifiers use different chopping frequencies such as 100 Hz .400 Hz, 1000 Hz etc. It should be noted that the input frequency must be less than one half the chopping frequency in order to prevent errors due to aliasing. The main disadvantages of chopper stabilized amplifiers are the clock noise, slow speed and variable AC input impedance. A simple chopper amplifier is shown in figure. The chopper is a SPDT (Single Pole Double Throw) switch. Depending on the excitation voltage the switch grounds the amplifier input and output terminals on periodic intervals. Then the chopped waveform is passed through the ac amplifier is used at the output side to reduce the noise. The input and output waveforms are shown in figure.
A type of chopper amplifier
Chopped waveform

Advantages of Chopper Stabilized Amplifiers:

1. Very low noise operation.
 2. Gives high stability.
3.Highly useful for EEG amplifiers to get high gain.

Electromagnetic Blood Flow Meter and its Advantages

- No comments
Electromagnetic blood flow meters are based on the principle of electromagnetic induction. According to Fleming's right hand rule, the EMF induced in the conductor under the influence of magnetic field is directly proportional to the velocity of motion of conductor. Here we consider the blood vessel carrying blood as the conductor. So here the velocity of motion is simply the blood flow through the blood vessel.
block diagram of electromagnetic blood flow meters block diagram
The block diagram of electromagnetic blood flow meter is shown. Here we simply use an oscillator of low frequency (up to 400 Hz) to drive the electromagnet which is placed in such a way that the magnetic field is perpendicular to the direction of blood flow. An EMF is induced across the blood vessel. In order measure this, a set of electrodes are placed across the blood vessel mutually perpendicular to both magnetic field and direction of blood flow.

The EMF induced across the blood vessel will be proportional to the velocity of blood, Lumen probes with varying diameters are used for the accuracy of measurement. The output of electromagnetic blood flow meter, which is in micro volts, is enhanced by the amplifier. For the average blood flow rate we usually use LPFs after the amplifier. Amplifier drift and electrode polarization may cause some problems with electromagnetic type flow meters.

Advantages of Electromagnetic Blood Flow Meters

1. Linear dynamic range
2. Electronics required are relatively simple
3. Almost any flow sensitivity can be measured
4. It has no mechanical limitation for high and low speed flow
5. The power requirements are reasonable.

Different Types of Defibrillators

- No comments

1. Manual External Defibrillators (M E D) 

These units are often used by the healthcare providers to diagnose a cardiac condition. The healthcare provider will decide what charge to use and will deliver the shock through paddles or pads on the patient's chest. These units are generally found in hospitals.

2. Manual Internal Defibrillators (M I D)

 They are identical to the external version except the fact that the charge is delivered through internal paddles in direct contact with the heart. They are found in operating theatres where the chest is likely to be open.

3. Automated External Defibrillators (A E D) 
These are simple to use units based on computer technology which is designed to analyze the heart rhythm itself and then advise the user whether a shock is required. The automatic units also take time to diagnose the rhythm, whereas a performer with a manual unit can diagnose and treat for the condition far more quickly. So the speed is less in an AED. Automated External Defibrillators are generally held by a trained personnel .Public access units are also available. An AED is external because the operator applies the electrode pads to the bare chest of the patient. Automatic refers to the unit's ability to automatically analyze the patients's condition and to assist this, some modern AEDs have visual displays to instruct the user. When turned on or opened, the AED will instruct the user to connect the pads to the patient. The pads allow the AED to examine the electrical output from the heart and determine if the patient is in a shockable rhythm. If the device determines that a shock is warranted, it will use the battery to charge its internal capacitor to deliver the shock. This system is not only safer, but also faster.

4. Semi automated External Defibrillators (S E D): 

These units are a compromise between a fully manual unit and an automated unit. Semi-automated External Defibrillators are usually mounted in an ambulance. These units are designed for use only by healthcare personnel and are capable of measuring blood pressure, blood oxygen saturation etc in addition to the basic function.

5. Implantable Cardioverter Defibrillators (I C D) 

It is also known as Automatic Internal Cardiac Defibrillators (A I C D). These devices are similar to pacemakers. They constantly monitor the patient's heart rhythm and automatically deliver shocks for various life threatening heart problems. The device is programmed to act according to the heart condition.

Defibrillator Working Principle

- No comments
Defibrillator Working Principle

The heart is able to perform the important function of blood pumping only through the synchronized of the heart muscle fibers is lost. A method to return the fibers to its normal synchronized working is called defibrillation. It consists of delivering a therapeutic dose of electric energy to the affected heart with a device called defibrillator. Defibrillators can be external, transvenous or implanted based on the nature of device used. Depending on this fibrillation is classified into atrial fibrillation of atrial muscles and the fibrillation of ventricles is called ventricular fibrillation.

Earlier mechanical methods such as heart massage for achieving synchronism of heart muscles were used. But the most successful method of defibrillation was proved to be an application of electrical shock to the area of the heart, if sufficient current is applied to stimulate all musculatures of the heart for a brief period of time fibrillation can be prevented. The early defibrillators used the alternating current which is transformed from normal line voltage up to 300-1000 volts from a power socket to the exposed heart by way of paddle type electrodes. This application of an electrical shock to resynchronize, the heart is called counter shock. If the patient does not respond, the method is repeated until defibrillation occurs. This method of defibrillation is called AC defibrillation. Nowadays this type of defibrillation is not used because it has some disadvantages. This technique was often unsuccessful and showed harm to the cells of heart muscle post mortem. The nature of the AC machine with a large transformer also made these units very hard to move and they tended to be very large units. So DC defibrillators are commonly used now.


A scientist named Bernard Lown used an alternating method which involved the charging of bank capacitors to approximately 1000 Volts and then delivering the charge through an inductance such as to produce a heavily damped sinusoidal wave of finite duration. This waveform is called Lown waveform (Figure) and is the standard for defibrillation. So DC defibrillation method, a capacitor is charged to a high dc voltage and is then allowed to discharge rapidly. The defibrillator is designed in such a way that the capacitor is rapidly discharged through electrodes across the chest of the patient. AC fibrillators cannot be used to correct atrial fibrillation effectively. But DC defibrillator can correct both atrial and ventricular defibrillation. This is an important advantage of DC defibrillators over the AC defibrillators. The DC method requires fewer repetitions and most importantly, it is less likely to harm the patient. The circuit representation of a DC defibrillator is shown below (Figure).

DC defibrillator
Lown waveform
The electrodes are the components through which the defibrillator for delivers energy to the patient's heart. Many types of electrodes such as hand-held paddles, internal paddles, pre-gelled disposable electrodes etc. ln general disposable electrodes are used in emergency conditions because they have the advantages such as increasing the speed of shock and improving defibrillation technique. Larger paddles create a lower resistance and allows more current to reach the heart .So larger paddles are desirable.

Figure shows a circuit diagram showing the simplest defibrillator desire depending on the inductor damping producing Lown waveform. In a defibrillator, the amount of electrical energy discharged by the capacitor may range from 100-400 Joules. The duration of discharge is 3-5 milliseconds, From the DC defibrillator discharge waveform (Also known as Lown waveform) shown in figure.
Simplest defibrillator
Numerous studies showed that a biphasic truncated waveform (BTE) was equally effective when requiring lower levels of energy to produce defibrillation. Biphasic defibrillation was originally developed and is used for implantable defibrillators. When applied to external defibrillators, the biphasic defibrillation decreases the energy level necessary for successful defibrillation. So this dual peak waveform of longer duration is having less risk of damaging the myocardium. Biphasic waveforms deliver current that first flows in a positive direction for a specified duration. ln the second phase the device reverses the direction of current. The biphasic shocks appear to achieve the same defibrillation success rates as monophasic waveforms but at a significantly lower energy levels. The waveform is shown in figure. Another DC defibrillator wave is the tapered delay wave (figure). It has lower amplitude of around 700-800 Volts and much longer duration than the other two types of waveform. Here the energy delivered to the patient by the defibrillator is proportional to the area under the square of the curve.

Biphasic truncated waveform

Tapered delay wave

Sunday, 19 August 2018

Secondary Database Searching & Hidden Markov Model

- No comments

Primary database search tools are effective for identifying sequence similarities. But analysis of output is difficult. So the main principle behind the development of secondary database is that by using them, we can share the structural and functional characteristics of the constituent sequences.
Different secondary databases are formed as a result of different analysis methods. HMMs, profiles, blocks, fingerprints etc are the different pattern recognition methods used in major secondary database. Some analysis methods are given below.

a) Fingerprints 

Within a sequence alignment, we can find several motifs (motif means a consecutive string of amino acids in a protein sequence, whose general character is repeated). In secondary database, we can store such motifs so that during searching it becomes easy to identify related sequences. Motifs are used to create a signature or fingerprint and stored in secondary database. The technique of fingerprinting is not commonly used.


Similar to protein fingerprinting, blocks may be used to search sequence database to find additional family members. Here blocks within the family are used to make, independent database searches .For a given sequence, the more blocks are matched, the greater possibility that the sequence belongs to that family.


Profile is a pattern recognition method in 2 databases. Profiles define which residues are allowed that given positions, which positions are highly conserved and so profiles helps in defining the full domain alignments.

d) Hidden Markov Model (HMM) 

It can determine the most likely MSA or set of possible MSAs. HMM is a probabilistic model consisting of a number of interconnecting states. HMMs have some limitations which lead to false matches.

The first approach for discovering disease related genes is the technique of positional cloning. Hence the chromosome related to the disease in question is stabled by analyzing a population of subjects. The whole process of positional cloning is time consuming.


- No comments
Database of multiple alignments  

Multiple alignment database is produced to have readily available high quality alignments. The advantages of using multiple sequence alignment is database searches is that more information is used, which results in higher sensitivity compared with pair wise searches.

PSI-BLAST is a hybrid database which uses elements of both pair wise and multiple sequence alignment methods. In PSI (Position Specific Iterated) BLAST, it allows automatic arrangement of position specific sequences. Main disadvantage of PSI-BLAST is that automatic iteration may lead to errors some times.

Multiple Sequence Alignment Methods

- No comments
Methods of producing Multiple Sequence Alignments (MSA):

1. Dynamic programming: 

There are different methods of producing a MSA.  The most direct method uses a dynamic programming technique to identify the globally optimal alignment solution. For proteins, the method of dynamic programming involves two set of parameters called gap penalty and substitution matrix. Here scores are assigned to the alignment of each pair of amino acids based on the similarity of amino acids' chemical properties and the evolutionary probability of mutation.

In MSA, for n-individual sequences, an n-dimensional equivalent matrix is formed in standard pairwise sequence alignment. The search space thus increases exponentially with increasing 'n'. The MSA program optimizes the sum of all the pairs of characters at each position in the alignment. It is called sum of pair score.

2. Progressive alignment construction 

Progressive alignment is the most widely used approach to multiple sequence alignments. It is also called hierarchical or tree method. It builds up a final MSA by pairwise alignments beginning with the most similar pair and progressing distantly related pair. All progressive alignment methods require two stages.  At first stage, the relationship between sequences is represented as a tree and in the second stage the MSA is built up.

The primary problem in progressive alignment is that when errors are made at any stage in growing MSA , these errors are then propagated through to the final result, Performance also degrades when all of the sequences in the set are distantly related. Progressive alignment methods are efficient enough even if we use about 1000 sequences.

3. Iterative methods:  

A major problem in the progressive alignment method is that the accuracy of alignment heavily depend on the accuracy of initial pairwise alignment. The iterative methods work similarly to progressive methods, but repeatedly realign the initial sequences and sometime add new sequences to the growing MSA.

4. Hidden Markov Models 

It can determine the most likely MSA or set of possible MSAs. HMM is a probabilistic model consisting of a number of interconnecting states. Typical HMM based methods work by representing an MSA as a partial order graph which consists of a series of nodes representing possible entries in the columns of an MSA. In this representation a column that is absolutely conserved is coded as a single node with many outgoing connections.

Multiple Sequence Alignment Definition

- No comments
Multiple sequence alignment is defined as an extension of pair wise sequence alignment to incorporate (unite together) more than two sequences at a time. Multiple alignment methods try to align all of the sequence in a given query set. Multiple alignments are often used is identifying conserved sequence regions across a group of sequences. Multiple alignments can also be used to find out evolutionary details.

Aim of multiple sequence alignment

• Multiple sequence alignment is mainly used to find out the similarity between sequences of a gene family.
• Sometimes multiple sequence alignments can also be used to express the dissimilarity between a set of sequences.
• In most cases the multiple sequence alignment can accurately find out biological data.

A multiple sequence alignment is a 2 dimensional (2D) table, in which rows represent individual sequences and columns represent the residue positions. The database of multiple alignments has a great importance. The power of multiple sequence analysis lies in the ability to find out related sequences from various species and to express the degree of similarity between them. The time taken to compute an alignment; increases exponentially with the number of sequences to be aligned.

Simultaneous alignment methods and progressive alignment methods are the two common procedures in multiple sequence alignments. In simultaneous alignment, all sequences are aligned with in a set at once are very time consuming. The progressive multiple alignment methods align sequences in pairs following the branching order of a family tree.

The most similar are aligned first and more distantly related sequences are added later. By exploiting likely evolutionary relationships, progressive multiple alignment methods are less time consuming.

Local Alignment and Global Alignment in Bioinformatics

- No comments

The technique of dynamic programming can be applied to produce Global alignments via Needleman-Wunsch algorithm and local alignments via the Smith-Waterman algorithm.


There are two general models to view alignments. The first model considers similarity across the full extent of the sequences (Global alignment). The second focuses on the regions of similarity in parts ofthe sequence only.(it is local alignment). A search for local similarity may produce more biologically meaningful and sensitive results than a global alignment.

Global alignment: Needleman Wunsch algorithms.

Global alignments attempt to align every residue in every sequence and they are most useful when the sequences in the query set are similar and of roughly equal size. Needleman and Wunsch algorithm is used for computing a global alignment between two sequences and it is based on dynamic programming. The algorithm proposed a maximum match path way that can be obtained computationally by applying some rules. Here cells representing identities are scored 1 and cells representing mismatches are scored 0. This process examines each cell in the matrix and finally summation of cells is started.  When this process is completed, the maximum match path way is constructed.

Thus in global alignment comparison of the two sequences over the entire length is done. The Needleman Wunsch algorithm for global alignment is time consuming to run if the sequences are long. This is a general algorithm for sequence comparison. It maximise a similarity score to give maximum score. Maximum match is the largest number of residues of one sequence that can be matched with another allowing for all possible deletions.

Local Alignment: - Smith-Waterman algorithm

Local alignments are more useful for dissimilar sequences that are suspected to contain regions of similarity or similar sequence motifs. Local alignment searches for regions of local similarity and need not include the entire length of the sequences. Local alignment methods are very useful for scanning databases. Smith Waterman algorithm is used for local alignments. Even if the two given sequences are dissimilar, there will be some local similarity between sequences. Smith Waterman algorithm is used to find out this local similarity.

The key feature of Smith-Waterman algorithm is that each cell in the matrix defines the end point of a potential arrangement. The algorithm thus begins by filling the edge elements with 0.0 (floating point) values. Now the remaining cells in the matrix are compared. Three functions are compared at a time and the maximum of these three is chosen. Once the matrix is complete, the highest score is located. It represents the end points of an alignment (with maximum local similarity).

In addition to these many score matrices have been devised that weight match between non-identical residues.


The MD (mutation data) score is based on the concept of point accepted mutation (PAM). 1 PAM indicates the probability of a residue mutating during a distance in which a point mutation was accepted per 100 residues. In a mutation data matrix, the amino acids are arranged by assuming that positive values represent evolutionarily conservative replacements. Within the matrix, values greater than zero indicate likely mutations, values equal to 0 are neutral (random) and values less than zero indicate unlikely mutations.


The most common task of sequence analysis is the detection of more distant relationships. BLOSUM matrices are derived in order to represent distant relationships more clearly. Here for each cluster, the sequence segments are arranged on the basis of minimum percentage identity. For each cluster the average contribution at each residue position is calculated. By setting different clustering percentages, different matrices can be produced.

Fast A and BLAST  

The fast A and BLAST programs are local similarity search methods that concentrate on finding short identical matches between sequences BLAST (Basic Local Alignment Search Tool) all segment pairs which are identical. It is also a computational programming algorithm tool to calculate local alignments. Fast A and BLAST search methods have comparatively low speed. Hence Gapped BLAST method can be used to improve search speed.

Dot Plot Sequence Alignment

- No comments

Pairwise sequence alignments can only be used between two sequences at a time but they are very efficient to find out the similarities. Pairwise comparison is a fundamental process in sequence analysis, which seeks out relationships based on sequence properties. Database searching is used to find out the sequence similarity searches. Pairwise sequence alignment methods are used to find the best matching piecewise (local) or global alignments of a two query sequences. The three primary methods of producing pairwise alignments are dot-matrix methods, dynamic programming and word methods. But of these methods, dot-matrix method is the popular one for pairwise alignments, and for multiple alignments, the other two methods are commonly used.

The most basic method of comparing two sequence is a visual approach known a dot-plot. Dot lot is a biological sequence comparison plot. The dot-matrix approach is qualitative and simple.

A dot plot is a graphical method that allows the comparison of two biological sequences and identifies the regions of close similarity between them. The simplest way visualize the similarity between two protein sequences is to use a similarity matrix own as a dot-plot. From dot-plot it is easy to visually identify certain sequence features such as insertions, deletions repeats, inverted repeats etc.

There are two dimensional matrices, which have the sequences of the proteins being compared along the vertical and horizontal axes. To construct a dot-plot the two sequences are written along the top row and leftmost column of a two-dimensional matrix and a dot is placed at any point where the character in the appropriate columns matches. In some implementations the size or intensity of the dot is varied depending on the degree of similarity of the two characters, So the matrix sequence segments appear as runs of diagonal lines across the matrix. The dot plots can also be used to assess repetiveness in a single sequence.

A manner of construction of dot plot matrix is shown below. Here for identical residue we mark it as a dot.
Dot Plot

Within a dot plot two identical sequences are characterized by a single unbroken diagonal line across the plot as shown above. But two similar, but non-identical sequences will be characterized by a broken diagonal and here the interrupted region indicates the location of sequence mismatches.

A pair of distantly related sequences with fewer similarities has a much noisier plot as shown above. Dot plot helps in comparison of sequences on the basis of evolutionary relation, structural similarity, and physiochemical properties etc.

Wednesday, 15 August 2018

DNA Sequence Analysis in Bioinformatics

- No comments
DNA Sequence Analysis in Bioinformatics:

The term DNA sequencing refers to methods for determining the order of nucleotide bases adenine (A), Thymine (T), Guanine (G) and Cytosine (C) in a molecule of DNA. In some special cases, letters besides A. T, C, and G are present in a sequence. These letters represent ambiguity. Of all the molecules sampled, there is more than one kind of nucleotide at that position. The advent of DNA sequencing has significantly accelerated biological research and helped scientific discovery in a great extent. The analysis of DNA sequence helps in many research areas such as forensic biology, biotechnology etc. With the advent of modern sequencing tools, the speed of sequences increased rapidly it helped major projects such as Human Genome Project. Sequence analysis and its collection can increase the scientists understanding of the biology of various organisms. Nowadays there are many tools and methods to provide sequence comparisons and sequence alignments. Usually it is an automated computer based examination. DNA sequence analysis basically includes the following areas.

DNA Sequence trace
A DNA sequence trace is shown below.

The rules of the International Union of Pure and Applied Chemistry (IUPAC) are as follows for representing different nucleotide bases.

• A = adenine
• C = cytosine
• G = guanine
• T = thymine
• R = G A (purine)
• Y = T C (pyrimidine)
• K = G T (keto)
• M = A C (amino)
• S = G C (strong bonds)
• NV =A T (weak bonds)
• B = GTC (all but A)
• D = GAT (all but C)
• H =AC T (all but G)
• V = G CA (all but T)
• N = A G C T (any)

a) The comparison of sequences in order to find similar and dissimilar sequence alignments.

b) The identification of gene structures, introns, exons, reading frames etc

c) Finding and comparing the point mutations or single nucleotide polymorphism (SNP) in organism.

d) Revealing the evolution and genetic diversity of organisms.

Gene Structure and DNA Sequences:

DNA sequence databases typically contain genomic sequence data which includes information about the untranslated sequences.

Features of DNA Sequence Analysis:

The main features of DNA sequence analysis are

Detecting Open Reading Frames (ORF):

ORF (Open Reading Frames) are the longest frame uninterrupted by a stop codon. Finding the end of an ORF is easier than finding its beginning. Actually ORF is used to encode a known gene and it consists of a series of DNA codons which includes an initiation codon and termination codon

Understanding the effect introns and exons: 

Introne is a sequence of DNA bases that interrupts the protein coding sequence of a gene and Exones are protein coding sequence of gene.

DNA Sequence assembly:

Another important field of sequence analysis is to determine the nucleotide sequence of a clone. Clone is actually a copied fragment of a DNA. Usually a sequence, which is a acceptable to all is produced with the help of an assembler program. The program generates the code according to weight given to each nucleotide position.

Effects of EST (Expressed Sequence Tag) data on DNA databases 

A large part of currently available DNA data is made up of partial sequences. They are called expressed sequence tags (ESTs). ESTs are randomly selected from a DNA library and are used to identify genes expressed in a particular tissue. EST production is highly automated and it results in missing bases. This gives rise to difficulties in sequence finding. ESTs are incomplete and some cases inaccurate. ESTs add a factor of faults to databases because there is always some degree of uncertainly.

EST analysis tools. 

There are many tools available for the analysis of ESTs.

a) Sequence similarity search tools.
b) Sequence assembly tools.
c) Sequence combining (clustering) tools.

Sequence similarity search tools: are used to search the similarity between sequences. In order to find the similarity of sequences different methods such as dot-plot representation etc are used.

Sequence assembly tools: When a search of databases reveals several ESTs matching with a sequence, normally the ESTs must be aligned with each other to reveal the sequence. This type of sequence alignment is to be called a sequence assembly. Ex:- TIGR assembler.

Sequence clustering tools: The main purpose of sequence clustering tools is to save the data base search time. Sequence clustering tools take a large set of sequences and divide them into clusters. A reliable and effective mechanism for clustering ESTs will save the database search time and analysis efforts. Such tools are valuable when large numbers of ESTs are generated. In Bioinformatics sequence clustering algorithms attempt to group sequences that are somehow related. For proteins homologous sequences are typically grouped into families.

Specialized Genomic Resources (Boutique Database)

- No comments

The purpose of specialized resources is to focus on species - species genomics and to particular sequencing techniques. The particular aim of such a data base is the integrated view of a particular biological system.

a) UniGene
* The collection represents genes from many organisms and each cluster relating to a unique gene and including related information corresponding to the gene.
* A valuable role of UniGene is in gene discovery.
* UniGene is also used for gene mapping projects and large scale gene expression analysis.

b)TDB — The TIGR Database

* These databases containing DNA and protein sequence, gene expression, protein family information etc.
* Also the data such as taxonomic range of plants and humans, role of cellular components are also present.

c) SGD (Saccharomyces Genome Database)

* SGD is an online data resource which contain information on the molecular biology and genetics of S.cerevisiae (Budding yeast).
* This data base provides internet access to the genome, its genes and their products etc.
* SGD helps the research field by uniting together functions to perform sequence similarity search tools.
 * The illustration of genetic maps using dynamically created graphical displays make the data base user friendly.

Genome Information Resources

- No comments
Genome Information Resources

DNA Sequence databases :

a) EMBL 

The EMBL Nucleotide Sequence Databases in bioinformatics is a comprehensive database of DNA and RNA sequences collected from the scientific literature and scientific applications. Also data are directly submitted from researchers and genome sequencing groups. It is the nucleotide sequence database from the European Bio-informatics Institute. The database is produced in collaboration with DDBJ(DNA Databank of Japan) and Gen Sank (USA). These groups collect a portion of total sequence data reported worldwide all new and updated entries are then exchanged between the groups. Information can be retrieved from EMBL using sequence retrieval system (SRS).
The rate of growth of DNA database is highly exponential. Normally the size of database almost doubles during a period of one year.

b) DDBJ (DNA Databank of Japan) 

DDBJ is the DNA Data Bank of Japan. It is the sole nucleotide sequence databank in Asia which is officially certified to collect, nucleotide sequences from researchers and to issue the internationally recognized accession numbers to data submitters. The primary purpose of DDBJ operations is to improve the quality of IRIS the International Nucleotide Sequence Database. It acts as collaboration with EMBL and Gen Bank. Here also data is produced, maintained and distributed at the national institute of Genetics. With the help of internet based data submission tools, sequences are collected worldwide.

c) GenBank (Genetic Sequence Databank)

Gen Bank is another DNA database and it incorporates sequences from publicly available sources. It is a database from the national center for Biotechnology Information (NCBI). It is one of the fastest growing store houses of known genetic sequences. It has a flat file structure that is an ASCII text file, readable by both humans and computers. Gen Bank database is having big size and hence Gen Bank is split into smaller discrete divisions. A Gen Bank release includes the sequence files and information derived from the database Since the Gen Bank database is split into smaller discrete divisions, fast and specific searches are possible. In addition to sequence data, Gen Bank files contain information like accession numbers and gene names, references to the published literature etc. Usually a Gen Bank includes the sequence files and the information derived from the database. Another feature of Gen bank is that it can be searched with user query sequences.

d) GSDB (Genome Sequence Data Base):  

It is produced by the National Center for Genome Resources at New Mexico. A complete collection of DNA sequences and information related to it is created, maintained and distributed by this data base. Also data are collected from producers and a quality check is done before distribution. The database is easily accessible via internet.

Secondary Databases in Bioinformatics

- No comments
Secondary databases are called so because they contain the analysis results of the sequences in the primary sources. SWISS-PROT has emerged as the most popular primary source and many secondary databases are based on SWISS-PROT due to its versatility.

Need for Secondary database

Simply it is a database that contains information derived from primary sequence data It will be in the form of regular expressions (patterns), Fingerprints, profiles blocks or Hidden Markov Models. The type of information stored in each of the secondary databases is different. But in secondary databases homologous sequences may be gathered together in multiple alignments. In multiple alignments there are conserved regions that show little or no variation between the constituent sequences. These conserved regions are called motifs. Motifs reflect some vital biological role and are crucial to the structure of function of protein. This is the importance of secondary database. So by concentrating on motifs, we can find out the common conserved regions in the sequences and study the functional and evolutionary details or organisms. Some of the common secondary databases are discussed below.

a) Prosite

It was the first secondary database developed. Protein families usually contain some most conserved motifs which can be encoded to find out various biological functions. So by using such a database tool we can easily find out the family of proteins when a new sequence is searched. This is the importance of PROSITE. Within PROSITE motifs are encoded as regular expression (called patterns). Entries are deposited in PROSITE in two distant files. The first file give the pattern and lists all matches of pattern, where as the second one gives the details of family, description of biological role etc. The process used to derive patterns involves the construction of a multiple alignment and manual inspection. So PROSITE contains documentation entries describing protein domains, families and functional sites as well as associated patterns and profiles to identify them.

b) Prints- fingerprint database

PRINTS is another secondary database. Most protein families are characterized by several conserved motifs. All of these motifs can be aid in constructing the `signatures' of different families. This principle is highlighted in constructing PRINT database. Within PRINTS motifs are encoded as un weighted local alignments. So a small initial multiple alignments are taken to identify conserved motifs. Then these regions are searched in the database to find out similarities. Results are analyzed to find out the sequences which matched all the motifs within the finger print. PROSITE and PRINTS are the only manually annotated secondary databases. Print is a diagnostic collection of protein fingerprints.

c) Blocks

The limitations of above two databases led to the formation of Block database. In this database the motifs (here called Blocks) ate created automatically by highlighting the and detecting the most conserved regions of each family of proteins. Block databases a fully automated one. Keyword and sequence searching are the two important features of this type of database. Blocks are ungapped Multiple Sequence Alignment representing conserved protein regions.

d) Profiles

Profile database is used to find out the most conserved regions in the sequence alignment. Profile is weighted to indicate modifications (in bioinformatics wording-INDELS) are allowed in the sequence. Indels may be the insertion of a new sequence or deletion from the sequence. Profiles are also known as 'weight matrices' to provide a means of detecting distant sequence relationships.

Sunday, 12 August 2018

Protein Sequence Database Examples

- No comments
The primary databases contain sequence data(nucleic acid or protein).

Protein sequence databases Examples.
The different protein sequence database examples are discussed below.

a. PIR (Protein Information resources): 

It is the largest, most comprehensive, annotated protein sequence database in public domain. It is a collection of sequences for investigating evolutionary relationships among proteins .The PIR database is split into four distinct sections. PIR 1 -PI R4 based on the manner in which the protein data are entered and their status. Normally the fully classified entries are given more importance and hence the entered in PIR 1. The sequences which are not fully classified are stored in PIR 2.Since the PIR entries are not fully classified they may contain redundant (excessive) information. The unverified entries are entered in PIR 3. The PIR serves the scientific community through online access, by distributing magnetic tapes etc.


It is a very helpful biological database of protein sequences. Swiss- Prot was developed by the Swiss Institute of Bioinformatics and European Bioinformatics institute. This database provides a high level of integration with other databases and has a very low level of redundancy (it means that less identical sequences are present in the database.) This database provides high level information including descriptions of the function of the proteins, its variants, structure of its domains etc. SWISS-PROT is one of the most popular protein sequence resources because of the quality of its entries. Also SWISS-PROT contains 70,000 entries from more than 5000 different species. The structure of SWISS-PROT makes computational access both straight forward and efficient. So SWISS-PROT is the most widely used protein sequence database in the world. Swiss-Prot functions as a minimal redundant information source. It means excessive data is not present- only the vital information is stored.

Swiss -prot provides descriptions of a non-redundant set of proteins including their function, domain structure, post-translational modifications and variants. It is tightly integrated with other databases. Swiss-Prot concentrates on model organisms of distinct taxonomic groups to ensure the presence of high quality annotation.

The Swiss-Prot group develops and maintains other databases including PROSITE, a data base of protein families, and ENZYME database of enzyme nomenclature.
 Structure of Swiss-Prot: Swiss-Prot emerged as a famous database due to the quality of its annotations (comments), structure and the way in which the data are stored. The common structure of database is given in table.

Two letter code in the entry
Each entry begins with an Identification line.
An additional identifier is provided by the Accession number
Give information about Date of entry, date of last modification etc. 
Description lines to describe the name by which the protein is known.
Give Gene Name.
Indicate Organism Species
Organism Classification information
R-line irovides a list of supporting references.
Comment lines to indicate the various protein details such as its function, subcellular location similarity to particular protein families etc.
These are called Database cross Reference lines to provide links to other bio-molecular databases, primary and secondary databases etc.
Give applicable Keywords
Feature table indicates the main regions of sequences concerned.
SQ line includes the sequence itself.
To indicate the end of entry.

c. TrEMBL ( Translated European Molecular Biology Laboratory). 

A special feature of TrEMBL format is that it contains translations of all coding sequences (CDS). The main aim of TrEMBL is to allow very rapid access to sequence data from genome projects. TrEMBL is a very large protein sequence database in Swiss-Prot format. It is generated by computer translation of the genomic information from the EMBL Nucleotide Sequence Database. Computer translation is not entirely perfect. So proteins predicted by the TrEMBL database can be hypothetical and many TrEMBL entries are poorly annotated (TrEMBL has two main sections designated SP-TrEMBL and REM-TrEMBL.

SP-TrEMBL: SWISS-PROT TrEMBL contains entries that are united together into Swiss-Prot. Swiss-Prot accession numbers are provided for all the entries of SP-TrEMBL.

REM-TrEMBL: Contains sequences that are not concerned to be included in SWISS-PROT.   

Composite Protein Sequence Databases:

Composite databases use a variety of different primary sources and are hence efficient to search. Different methods can be used to create composite resources. Composite databases render sequences searching much more efficient because they avoid the need to interrogate multiple sequences. The main composite databases are,

a) NRDB (Non-Redundant Database)
b) OWL

This database has the advantage of containing fewer errors than many Other composite databases. Different composite databases use different primary sources. 

Central Monitoring Console in ICU

- No comments
Central Monitoring Console in ICU:

In modern central monitoring console units, the entire information of different patients from different bedside monitors are collected and displayed. With this information the operator in the central monitoring console can give guidelines to the physicians and nurses so that the patients with abnormalities in various physical parameters can be given care separately. So, all the measured physical parameters are routed from each on bedside monitors to the central nurse's console. The CMC consists of an array of multi-channel oscilloscopes, digital tachometers etc. The typical block diagram of CMC in ICU is shown below.

Here the electrodes measure different physiological parameters from different patients. They are amplified by high gain op-amps and are locally displayed on bedside monitors. Also digital readouts and paper readouts are provided. Also local alarms are provided to alert the staff if the condition of patients becomes abnormal. The various parameters from each BSM is transmitted to central monitoring console by suitable transmission paths. The staff at the central monitoring console can continuously monitor the patients and the number of staffs at the bedside monitors can be reduced. The data can also be stored in a digital computer.


In modern central monitoring console units, the entire information of different patients from different bedside monitors are collected and displayed.

The staff at the central monitoring console can continuously monitor the patients and the number of staffs at the bedside monitors can be reduced.

Tuesday, 7 August 2018

Intensive Care Unit and Critical Care Unit

- No comments

Intensive Care Unit and Critical Care Unit or Coronary Care Unit are specific care units utilized as a part of doctor's prescription in different nations that gives intensive care medicines. Excellent ICUs are equipped with medicinal devices, for example, mechanical ventilators, bedside monitors, digital cardiotachometers, pacemakers, defibrillators, dialysis instruments and so on. The biological data related with the patient from the bedside monitors can be dissected by the concerned doctor or nurse to give better care. The quality of care of an ICU relies upon the patient to nurse ratio. For a decent ICU a proportion of 2 patients to a nurse is suggested. Likewise the different parameters from various ICU units can be sent to a central monitoring console for detailed analysis and care (figure shown).

 Bedside monitors and CMC

CCU (Critical or coronary) care unit is a unique care unit managing with the care of patients with diseases associated with heart(such as heart attack).The principle highlight of CCU is the accessibility of telemetry or the consistent monitoring of ECG in order to check the proper functionality of heart.


Cardio tachometers

The cardio tachometers are used to count the heart rate of patients. For a normal human the heart rate is 72 pulses minute. By using digital cardio tachometers which directly display the heart rate, we can examine the health of patients. The cardio tachometers can be of analog or digital type.


The block diagram representation of an analog cardio tachometer is shown below (figure).The analog cardio tachometers are not commonly used now a day. They provide a DC voltage proportional to the patients' heart rate. This DC voltage can be displayed on analog or digital voltmeter.

 The different blocks are explained below. 


The ECG of patient under test is measured by using a proper electrode and applied to a differentiator. The function of differentiator is to avoid double counting. The basic principle -of cardio tachometer is to measure the number of R-waves in the ECG. Since for each heart pulse the R-wave have the highest amplitude level, it can, provide the heart rate. But in some patients T-wave or P-wave may be predominant. It may produce double counting false. But by using differentiator we can avoid this error. This is because even if the T-wave or P-wave is large, the fast changing R-wave will always produce a large output voltage than P-wave or T-wave due to the effect of differentiator. This block is also called R-wave discriminator.

2.Level Detector 

Since each R-wave can produce a specific voltage, the output of R-wave discriminator is applied to a level detector .The level detector produce an output voltage change only when the predetermined input voltage level is exceeded.(That means it will produce an output voltage change for each R-wave).The differentiator and level detector stages are collectively called as QRS-discriminators.

3.Mono stable multivibrator 

The o/p of level detector is corresponding to no. of R-waves. The output from level detector is applied to the mono stable multi vibrator. So an output pulse is generated for each R-wave. These pulses have constant duration. But the pulse repetition rate will vary with respect to the heart rate.


Integrator averages the pulses applied to its input from the mono stable output. In a mono stable multi vibrator one o/p pulse is generated for each R-wave and the pulses have constant width. So the DC o/p voltage of integrator will be proportional to the number of R-waves per unit time.

5.Digital /analog voltmeter

Even though we are using analog technique the o/p from the integrator is applied to a digital voltmeter. For more indication the o/p from integrator can also be applied a tone indicator which produces specific tone corresponding to each heart rate and a lamp indicator in which the LED glows corresponding to the heart rate.


Here ECG is taken from patient using suitable electrode and passed through differentiator, level detector and mono stable circuits as in the case of analog cardio tachometers. The difference between analog and digital tachometer is that the o/p from the mono stable is applied to a 4- in -1 generator. The 4- in -1 generator generates 4 o/p pulses corresponding to one pulse from the mono stable multivibrator. The o p, from the 4-in -1 generator is applied to one of the AND gate inputs and the other input is the o/p from a 15 s time base. So the AND gate will be on for -15 seconds. Since AND gate will be ON for 15s, the gate will pass the pulses to a digital counter connected to its 6-1p. So the counter counts the pulses from 4-in -1 generator within 15 s. Suppose 17 pulses are generated from the mono stable within 15s.These 17 pulses will be converted in to 68 pulses by the 4- in- 1 generator.(17*4).So the counter will show the count rate as 68 pulses .After 15 seconds, the counter o/p will be displayed and updated by the 15 s time base. Sometimes the gating error of the AND gate can create certain errors in a digital cardiotachometer. Digital tachometers which can count from 27 to 199 beats per minute are available. They have less power consumption. Also accuracy can be enhanced by using a programmed read-only memory. The block diagram of Digital Cardiotachometer is shown below.


Since the heart rate is an important physiological parameter, it has to be monitored continuously. If the heart rate crosses the limit in either direction, it has to be highlighted. In cardio tachometers, alarm circuits are provided on bedside monitors to warn the staff on an emergency condition. Here the mechanical arrangement of alarm is designed in such a way that it will turn ON when heart rate is too low or too high. A metal vane connected to the, meter pointer trigger the alarm circuit when pointer moves on either side exceeding a limit. When the pointer exceeds the limit, the metal vane will blind the photocell assembly .So the resistance will increase and it causes triggering of alarm circuit. Same condition occurs when the pointer exceeds limit in opposite direction. Here also the metal vane will blind the photocell assembly to trigger alarm (figure shown below).