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Carbon Nanofoam Structure and Functions

Abstract Carbon nanofoam is the fifth allotrope of Carbon after graphite, diamond, fullerene (e.g., C-60 molecules), and Carbon nanotubes. It was discovered in 1997 by Andrei V. Rode and his team at the Australian National University in Canberra, in collaboration with Ioffe Physico-Technical Institute in St Petersburg. The molecular structure of Carbon nanofoam consists of Carbon tendrils bonded together in a low-density, mist like arrangement.
This paper talks about the physical structure, chemical properties, preparation methods and applications of Carbon nanofoam. The most unusual property of Carbon nanofoam is its ferromagnetism; it gets attracted to magnets, like iron. At a temperature as low as -183 ÌŠC, Carbon nanofoam behaves like a magnet. Also, the foam is a semiconductor, making it attractive for device applications. The reason for the foam’s magnetic property has been explained in the paper.
Carbon nanofoam is hence the first pure-Carbon magnet and also one of the lightest known solid substances (with a density of ~2 mg/cm3), when used along with aerogel. The Carbon nanofoam is believed to remove “magnetic prejudice” among the known elements, the idea than an element should be stereotyped as either magnetic or nonmagnetic.
1. INTRODUCTION Carbon nanofoam was discovered by 1?Andrei V. Rode and co-workers, in collaboration with Ioffe Physico-Technical Institute in St Petersburg at the Australian National University in Canberra in the year 1997. It is the fifth allotrope of Carbon after graphite, diamond, fullerene and Carbon nanotubes.
The molecular structure of Carbon nanofoam consists of Carbon tendrils, bonded together to form a cluster- like assembly of low density in a loose three- dimensional web pattern. The width of each cluster is about 6 nanometers, consisting of about 4000 Carbon atoms. These Carbon atoms are linked in the form of graphite- like sheets but consist of heptagonal structures included among the hexagonal patterns, giving it a negative curvature, (Figure 1(a)) unlike the Buckminster fullerenes [1] in which the inclusion of pentagonal structures gives the Carbon sheet a positive curvature. The density of Carbon nanofoam is approximately 2 mg/cm3, which makes it one of the lightest known solid substances, the other being aerogels whose density is about 100 times more than that of Carbon nanofoam [1].
According to Rode and his colleagues [1], nanofoam contains a number of unpaired electrons due to the Carbon atoms with only three bonds, found at topological and bonding defects. This gives rise to the most unusual feature of Carbon nanofoam, which is that it is attracted to magnets. Moreover, below ˆ’183°C Carbon nanofoam acts as a magnet itself. Another property of Carbon nanofoam is that unlike aerogels, Carbon nanofoam is a poor conductor of electricity.
The clause for the magnetic property of Carbon nanofoam is that only freshly produced Carbon nanofoam is ferromagnetic; Carbon nanofoam is strongly attracted to a permanent magnet at room temperature, initially. This room temperature ferro- magnetic behavior disappears after a few hours of preparation of the Carbon nanofoam, when the temperature eventually fluctuates to go above the room temperature. However, the ferro-magnetic property persists at lower temperatures.
Depending on the pressure of the ambient Argon gas inside the chamber where high- pulse, high- energy laser ablation [3] [4] [5] and deposition of Carbon vapors is performed, different Carbonaceous structures are formed. At a pressure of 0.1 Torr*, diamond- like Carbon films are formed. As the pressure is increased to greater than 0.1 Torr, diamond like Carbon- nanofoam is produced. The density of the Carbon nanofoam depends on the density and the polymerization chemistry used during the sol-gel process [3] [4]. The particle diameter of low-density foams is the largest, which is up to 100 nanometers, with a pore size of at least 500 nanometers. The high- density Carbon foams have pores of size less than 1000-Angstrom Units and the particles are ultra-fine, the density being approximately 0.8 grams/cubic centimeter. Electrically conductive Carbon nanofoams are also under production, which has many properties of the traditional aerogel material. Prepared by sol- gel methods, these materials are available in the form of monoliths, granules, powders and papers. The foams prepared by these methods are typically of low density, continuous porosity and high capacitance.
The most intriguing property of Carbon nanofoam is its Ferro magnetism (Figure 1(b)). The reason for the existence of this unusual property attributed to an allotrope of Carbon, which is conventionally believed to be a non- magnetic element, is due to the complex microstructure of the nanofoam. Few researchers claimed that the ferromagnetism is due to the presence of traces of iron and nickel impurities in their foam. Later they calculated that the small amounts of these magnetic materials could only account for 20% of the strength of the ferromagnetic fields in the foam and concluded that the ferromagnetism is an intrinsic property of this allotrope of Carbon. The unpaired electron that does not form a chemical bond in the 7- corner, 7- edged polygons present in the structure of Carbon nanofoam has a magnetic moment, which is suspected to be the reason of its magnetism.
*1 Torr is approximately equal to 1 mmHg; 1 Torr = 133.322368 Pascal
Due to the magnetic properties of Carbon nanofoam, it can be used in a number of applications namely, medicine, optics, fuel cells and other electronic devices. They are also being used as lightweight, high temperature insulation materials, absorbents and coating agents and as electrodes for water deionization cells. In biomedicine, Carbon nanofoams are used as tiny ferromagnetic clusters, which could be injected in blood vessels, in order to increase the quality of magnetic resonance imaging. Another application of Carbon nanofoams is in spintronic devices, whose operations are based on the material’s magnetic properties.
The researchers also have preliminary indications that the novel magnetic behavior also occurs in another nano-compound made of boron and nitrogen, two other elements that are ordinarily non-magnetic.
The following parts of this paper discuss in detail, the
Molecular Structure
Synthesis methods
Properties, and
Applications of Carbon nanofoam.
2. STRUCTURE OF CARBON NANOFOAM Carbon nanofoam consists of Carbon atoms bonded by both sp2 and sp3 hybridizations, unlike the other allotropes of Carbon such as graphite and diamond which have only sp3 hybridization and C60 and Carbon nanotubes that have only sp2 hybridization [7]. Around 4000 such Carbon atoms are bonded together in the form of a cluster-like assembly of low density. In other words, these Carbon atoms are bonded in the form of graphite-like sheets but consist of heptagonal structures included among the hexagonal patterns, giving it (Carbon nanofoam) a hyperbolic pattern, as proposed for schwarzite[6]
The percentage distribution of the sp2 and sp3 hybridizations can be controlled by during the synthesis of the nanofoam. High pulse-rate Laser Ablation method for the synthesis of Carbon nanofoam by A. V. Rode et al [1] demonstrates that there are two types of particles in the foam and that here is a small amount of particles with a high sp2 fraction (~0.9) of graphite-like bonds, due to crystalline graphite used in the experiment. Particles with a fraction, generally lower than 0.8 sp2 are inferred to consist of amorphous Carbon with a mixture of sp2 and sp3 bonding. Particles with lower sp2 content and a higher Plasmon energy are more “diamond-like”, as they have higher density and a higher fraction of sp3 bonds. Upon measurement, it has been observed that these is a high sp3 content at the edges of the foam and at the edges of the cluster, which is a clear indication that the sp3 bonding atoms are located at the surface of the clusters and that the connections between the clusters are due to the sp3 bonding.
3. SYNTHESIS OF CARBON NANOFOAM The synthesis of Carbon nanofoam is done on a laboratory scale and is not produced industrially, in bulk. Two methods are adapted for the preparation of Carbon nanofoams, depending on different types of requirements such as particle size, density, resistivity, etc. The two methods are listed and explained below.
3.1. Laser Ablation
Laser ablation is the process of removing material from a solid (or occasionally liquid) surface by exposing it to radiation with a laser beam. Depending on the flux density of the laser, the effect of laser ablation varies. For a more clear description; at low laser flux, the material is heated by the absorbed laser energy and evaporates or sublimates. At high laser flux, the material is typically converted to plasma. Usually, laser ablation refers to removing material with a pulsed laser, but it is possible to ablate material with a continuous wave laser beam if the laser intensity is high enough.
High-repetition-rate laser ablation and deposition of Carbon vapors results in the formation of quite different Carbonaceous structures depending on the pressure of the ambient Ar gas in the chamber. Diamond-like Carbon films form at a pressure below 0.1 Torr whereas a diamond-like Carbon nano-foam is created above 0.1Torr. The creation of particular molecular structures involves “atom-to-atom” attachment in appropriate physical conditions at an appropriate rate.

3.1.1. Experimental Setup
The experimental setup of the experiment conducted by E.G. Gamaly and piers is as follows: a 42-W, 120-ns pulse-width Q-switched Nd: YAG laser (λ = 1.064 mm) with variable repetition rate of 2-25 kHz was used. Laser of intensity approximately 109 Watts/cm2, averaged over the pulse duration was created on the glossy Carbon target, keeping the repetition rate fixed at 10 kHz and focal spot scanned over a 2X2 cm area of the target surface.
3.1.2. Formation of Carbon Nanofoam in Ar ambient temperature
The diamond-like Carbon (DLC) films is deposited in vacuum of approximately 106 Torr.
Transformation to a different form of Carbon material occurs in an Ar-filled chamber at a pressure around 0:1Torr. At this pressure, the mean free path for collisions of the evaporated Carbon atoms is in the order of 1 cm. Thus, Carbon-Carbon and Carbon-argon collisions in the chamber start to play a dominant role in the formation of Carbonaceous structures in Ar-filled chamber.
The high-repetition-rate laser evaporation of a Carbon target in a 1-100 Torr Ar atmosphere produces a higher evaporation rate of Carbon atoms and ions than conventional laser ablation techniques.
The resulting increased average temperature and density of the C-Ar mixture in the experimental chamber increases the probability of the formation of higher energy Carbon-Carbon bonds.
The resulting increased collision frequency from the above deposition conditions encourages diffusion-limited aggregation of Carbon atoms into fractal structures, and the formation of low density Carbon foam.
Figures 3.1.2. (a) and 3.1.2. (b) show the scanning and transmission electron microscope images respectively, showing the free-standing Carbon foam. These images are scaled to 1 mm and 100 nm respectively.
The analysis of these images reveal that the foam represents a fractal-like structure which consists of Carbon clusters with the average diameter of 6 nm randomly interconnected into web-like foam.
The foam looks like a capricious mixture of “strings of pearls”. [3]
Initially, the flow of atomic Carbons is created by the laser ablation near the target surface. After the chamber is filled with an inert ambient gas, it results in the collision of Carbon atoms with the ambient gas atoms, as the Carbon plume expands. Hence, the Carbon atoms collide, diffuse through the gas, exchanging their energy, and finally cool down to the average Carbon-gas temperature.
3.2. Sol Gel Process
The sol-gel process, also known as chemical solution deposition, is a wet-chemical technique widely used in the fields of materials science and ceramic engineering. Such methods are used primarily for the fabrication of materials (typically a metal oxide) starting from a chemical solution (or sol) that acts as the precursor for an integrated network (or gel) of either discrete particles or network polymers. Typical precursors are metal alkoxides and metal chlorides, which undergo various forms of hydrolysis and polycondensation reactions.
Carbon nanofoam is also prepared from the pyrolysis of organic precursors, such as organic aerogels produced through sol-gel processes (such as resorcinol formaldehyde sol-gels) (Figure 3.2.). The sol-gel solution is cast into the desired shape and after the formation of a highly cross-linked gel the solvent is removed from the pores of the gel. The remaining rigid monolithic shape consists of covalently bonded, nanometer-sized particles that are arranged in a 3-dimensional network. Precursor RF gels can be applied to a fine Carbon felt which is Carbonized to form Carbon nanofoam electrodes [9].
The Carbon nanofoam thus prepared usually has low density and very high specific surface areas (up to ˆ¼1200m2 g-1), and they can be produced in different forms, such as monoliths, fine particles or films. The final shape and properties depend strongly on the sample history, as is the case with all amorphous Carbons.
4. PROPERTIES OF CARBON NANOFOAM Many of the properties of Carbon nanofoams match with those of the traditional aerogel materials. Carbon nanofoams are available in the form of monoliths, granules, powders and papers. They are electrically conductive, synthetic and lightweight foams in which the solid matrix and pore spaces have nanometer-scale dimensions.
Prepared by sol-gel methods, nanofoams typically have low density, continuous porosity, high surface area, and fine cell/pore sizes. The foams are also electrically conductive and have a high capacitance. Standard densities of Carbon nanofoams range from 0.25 to 1.00 g/cm3. Carbon nanofoams precursors can be infiltrated into a Carbon fiber mat that, when Carbonized, will result in paper-like electrode material 0.007 to 0.050 inches thick.
Morphology examination by scanning electron microscope shows an open cell structure and continuous porosity. The particle size and pore spacing is a function of density and the polymerization chemistry used during the sol-gel process. Low density Carbon nanofoams (~0.25 g/cm3) have the largest cell/pore size with particle diameters of up to 100 nm and pores at least 500 nm. High density Carbon foams (abt. 0.8 g/cm3) have ultra-fine particles and pores of less than 1000Å.

The nanofoam contains numerous unpaired electrons, which Rode and colleagues propose is due to Carbon atoms with only three bonds that are found at topological and bonding defects. This gives rise to what is perhaps Carbon nanofoam’s most unusual feature: it is attracted to magnets, and below ˆ’183 °C can itself be made magnetic.
4.1. Ferro magnetism of Carbon nanofoam
It is a well-known fact that Carbon and its allotropes are among those materials which do not get attracted to magnets. Although, it has been discovered that Carbon nanofoam is attracted to magnets, and below ˆ’183 °C can itself be made magnetic. This behavior of Carbon nanofoam is unusual as against the magnetic property generally attributed to Carbon. However, at room temperature, the nanofoam’s magnetization disappears a few hours after the material is produced.
The reason for the magnetic behavior of Carbon nanofoam is discovered to be its molecular structure; it consists of a number of unpaired electrons due to the Carbon atoms with only three bonds that are found at topological and bonding defects. The unpaired electrons contribute towards the existence of magnetic moment in the nanofoam, which is believed to be the reason for its ferro magnetic character.
Detailed explanation
Speaking in terms of magnetic susceptibility, in general, all known Carbon allotropes exhibit diamagnetic susceptibility in the range of χ =ˆ’(10ˆ’5-10ˆ’7) emu/g Oe with the exception of:
Polymerized C60 prepared in a two-dimensional rhombohedral phase of χ= (0.25ˆ’1.3)*10ˆ’3 emu/g Oe (depending on the orientation of the magnetic field relative to the polymerized planes) which shows ferromagnetism
The disordered glass-like magnetism observed in activated Carbon fibers due to nonbonding π-electrons located at edge states, and
The unusual magnetic behavior observed in single wall Carbon nanohorns ascribed to the Van Vleck paramagnetic contribution.
Although ferromagnetism in polymerized C60 is noteworthy, the exceptionally large magnetic signal in Carbon nanostructures such as Carbon nanofoam remains a case of special interest.
In order to study the ferro magnetism of Carbon nanofoam, an experiment was conducted by Rode and his colleagues. They prepared Carbon nanofoam by high-pulse-rate laser ablation of an ultrapure glassy carbon target in a vacuum chamber made of stainless steel, filled with high-purity (99.995%) Argon gas, inside a 2 inch cylinder made of fused silica (SiO2). This setup results in the formation of carbon nanofoam, with a combination of sp2 and sp3 hybridization. The reason for the magnetic character of Carbon nanofoam was then discovered to be the ferromagnetic interaction of the spins of the unpaired electrons, separated by sp3 centers. [6]
A possible mechanism for magnetic moment generation would be a simple indirect exchange interaction through conduction electrons located on the hexagons. Low temperature magnetization curves indicate a saturation magnetization of approximately 0.35emu/g at 2 K. [10]
5. APPLICATIONS OF CARBON NANOFOAM Carbon nanofoam is one of the lightest known solid substances till date. Hence, it finds its application in a number of fields. Although there are no immediate applications of Carbon nanofoams, a few of the possible areas where there can be applied are as follows:
They could be used in spintronic devices, which are based on a material’s magnetic properties.
In biomedicine: the Nano metric scale ferromagnetic clusters could be injected into blood vessels to enhance magnetic resonance imaging. It could also be implanted in tumors, where it could turn radio waves into a source of heat that would destroy the tumor but leave surrounding tissue unharmed.
Carbon nanofoam can replace the nanofoams of other metals because of its low density, high conductivity, light weight and also its ferro magnetic property.
As coatings or absorbents in specialty optics
As flexible electrodes for deionization and fuel cells
Carbon nanofoam paper
Making of High-Sensitivity Ultrasonic Transducer in Air
High-performance metal-air batteries
Spintronics, meaning spin transport electronics is also known as magnetoelectronics. It is an emerging technology which, in addition to its fundamental electronic charge, exploits both the intrinsic spin of the electron and its associated magnetic moment, in solid-state devices. Spintronic devices find their application in perhaps the most important computer subsystems: random access memories and high density non-volatile storage media. Hence in order to develop large memories on a small chip, making the chip as light weighted as possible is also very important. This is where the use of carbon nanofoam gives the desired result.
Carbon nanofoam paper is another interesting application of carbon nanofoams. Due to its composition, carbon nanofoam paper has proven very difficult to cut using traditional methods such as metal blades. It was found that using 100 W of power at a speed of 250 inches per minute (IPM) the 0.0075-inch thick carbon nanofoam paper was cleanly cut. [11]
For a high-sensitivity ultrasonic transducer in air, nanofoam can be considered to be applied to its acoustic matching layer. Since nanofoam has extremely low acoustic impedance, it is effective for the acoustic matching layer of an ultrasonic transducer in air. The sensitivity of the developed ultrasonic transducer can be made up to about twenty times higher than that of a conventional ultrasonic transducer in air. [12]
The desirable structural characteristics of carbon nanofoams can be exploited to design and produce electrocatalytic structures for O2 reduction that will enable high-performance metal-air batteries. While the native carbon nanofoam structure exhibits modest activity for O2 reduction, further functionalization of the nanofoam is necessary to achieve technologically relevant performance. [13]
6. CONCLUSION In conclusion, this term paper throws light on a recently discovered allotrope of carbon called as Carbon Nanofoam, whose molecular structure and properties are different from the other allotropes of carbon such as graphite, diamond, C60, amorphous carbon, carbon nanotubes and fullerene. Carbon nanofoam is found to be one among the lightest known solid substances, which gives it an advantage over other substances in a number of varied applications.
The most intriguing feature of carbon nanofoam is its magnetic property. This novel magnetic behavior found in carbon nanofoam has made many renowned scientists and researchers rethink about what makes a material magnetic, since ferro-magnetism is not one of the attributed properties of carbon in any of its forms. Furthermore, this ferro-magnetic characteristic of carbon nanofoam, along with its other characteristics such as extremely low acoustic impedance, low density, continuous porosity, high surface area, fine cell/pore sizes, electrical conductivity and high capacitance is believed to have wide applications in the developing current technology whose motto is “The smaller the better”!

Strategies of Gene Sequencing

Databanks
When a gene is sequenced for the first time, it is submitted to a databank such as DNA Data Bank of Japan (DDBJ), GenBank or European Molecular Biology Laboratory (EMBL). The submission of the nucleotide sequence databanks via the internet, undergo a simple automatic process which done electronically with web-based procedures. The databanks that share their information on a day-to-day basis can be considered as one and the same, hence it merely necessary to choose one of them to submit the sequence.
When comparing EMBL with GenBank, both of the databanks enclose the similar data and computer-readable, however the entries in GenBank is different, some difficulty will encounter when switching from one to the other. By the way, in those Databanks, the accession number (AC) has a significant usage, it is the most useful way of retrieving a specific sequence from the databank as well as the one that is stated in publications. It is said to be the accession number is distinctive to that certain sequences, instead to the specific gene or locus. Hence, the accession number is the same in each of the different databanks for any known sequence. Yet, the same sequence from different variants or strains of the same species may have different accession numbers.
By using some specific tools such as BLAST, different versions of a particular gene can be search for in the databank by entering gene name or using a known sequence and search for similarities. A substantial amount of annotation is listed for each entry to make the sequence information more beneficial. The annotation includes the info about the origin of the sequenced DNA, the identification and the computer prediction of the protein sequence to some extent of open reading frame, intron or exon boundaries and the information about expression signals, motifs and structural elements. The annotation can be used to define the function of the gene and goes into the feature table (FT) to read by Artemis in order to produce a visual display of the features of the sequence.
UniProt is a databank of protein sequences which generally used to provide the info about the 3D formation of the protein and cross-references to several other databases such as Prosite and Pfam. In the protein sequence databanks, the data about protein sequences can be divided into two types, which are physical and predicted. The former which derived from direct protein sequencing is indicated as the physical information of protein sequences. While, the former which derived by computer translation of DNA sequences and may not having direct evidence that prove the protein is actually exist is indicated as predicted information of protein sequence.
Sequence Analysis
1. Identifying Coding Regions
A coding region in a gene is identified in order to translate into a protein. Introns are not necessary for the translation process, only exons are used for translation. Hence, the cloned fragment, the gene with bacterial in origin and cDNA eukaryotic gene can ignore the introns.
An open reading frame (ORF) is referred to the region of a sequence which code for a protein that must not have the presence of stop codons. The location of stop codon indicates the end of the protein. The reading frame with lots of stop codons is not used for translation. ORF can be identified using computers to code for a protein and directly translate the DNA sequence into a protein sequence. ORF is search in a sequence because mRNA is able to translate into any three different reading frames protein.
In addition, an ORF is also explained as the distance between a start codon and the first stop codon in the same reading frame. Although ATG is the start codon in DNA, codons such as GTG, TTG or CTG are used as start codon mainly in bacterial. The finding of the region between two stop codons is carried out, rather than looking for the region between start codon and the first stop codon due to the uncertainty to identify the real start codon.
2. Expression Signals
The coding region of an open reading frame (ORF) is considered useless if the region of the DNA does not transcribe in the correct direction. Hence, it is significant to identify a potential transcription start and stop codons. In prokaryotes, especially bacteria, it has a promoter with two conserved consensus regions: the -35 region and -10 region that located upstream of the promoter. Genes are transcribed at these promoter sites: TTGACA at -35 region and TATAAT at -10 region by RNA polymerase. Generally, the distance separates both of the regions can be different by a few bases, a putative promoter is labeled when the sequences close to a consensus promoter in the right place is found. However, a putative promoter sometimes cannot be find due to the gene may be transcribed as part of an operon or the changes of the specificity of RNA polymerase by substitution of a different sigma factor. Moreover, the putative promoter sites are necessary to view computer predictions due to it is just a beginning of an investigation and it able to provide clues that need to be confirmed by more direct, experimental evidence.
While, in eukaryotes, ‘boxes’ or ‘response element’ with TATA- box, GC- box or CAAT- box are used to mediate the binding of RNA polymerase. The distance between those elements are not regular which is more complicate than the finding the transcription start site in the bacterial. So websites are available to predict the transcription start sites of an organism and it also used to identify consensus sequence from the same organism’s known promoters. In order to identify the RNA polymerase binding sites, the sites of which regulatory proteins attach to the DNA are search primarily. The proteins contained well-conserved, characterized and recognition sequences which have the transcription activating and repressing functions.
In both prokaryotes and eukaryotes, different regulatory proteins bind to the ‘boxes’. DNA sequences for each of these boxes can be screened, they provide evidence about the regulation of the significant genes and their possible function.
Sequence Comparisons
1. DNA Sequences
The query sequence aligns with the second sequence to identify whether the sequence is identical or similar to other sequence that has been determined. Computer is used to calculate the number of bases that match in order to determine the characteristics of the two sequences. The query sequence slides along the sequence which being compared with to find out the best match because the two sequence may possibly be vary in lengths or may not start at the same site. Yet, query sequence may have one or more gaps within it when comparing to the second sequence. This happened due to a difference between the sequences when comparing the genes from different species or one of the sequences is incorrect. By adding or removing a single base can affect the simplistic approach to non-viable. A very small difference between query sequence and the sequence in the databank can make our sequence line up perfectly but also can make the rest of the sequence not match at all. Therefore, the computer is used to introduce gaps into one or both sequences in order to come up with the best possible match between the two sequences.
The system used to lining up the two sequences is incorporates with a gap penalty. Every single time a gap is presented into any sequence, the score will decreased. This type of algorithm will need a higher proportion of computer power as the sequences getting longer. Score has to be calculated for each position with all likely combinations of gaps. The query sequence is meant to be comparing with all sequences in the databank and not just comparing with a single other sequence, however it requires even more computational power. FASTA is the program that generally used to speed up the comparing process. The sequence that we are searching for is cut into small fragments which known as ‘words’. These ‘words’ is used to select the two ideal alignment and then followed by computing a score for the optimal alignment.
In addition, the mechanism of BLAST is to find a very short matches and followed by extending those match outward till the score drops below a fixed value. High-scoring Segment Pairs (HSP) is refers to the complemented pair of sequences above a certain length, it has started with those with the highest score. From a BLASTN search of databank with a query sequence, the first column classifies the sequence that matches by accession number (AC). While in the second column, it shows the annotation of the sequence. Lastly, the most significant column is the column labeled with ‘E value’ which put up an estimation for the probability to each match occurring by chance. It is said to be a low E values with a high negative logarithm referred to a strong match.
2. Protein Sequences
When searching an unknown sequence from databanks, protein sequence is used instead of nucleotide sequence. The protein level is searched due to the degeneracy of the genetic code, related proteins are usually more conserved than DNA coding sequence. The coding sequences in the DNA databanks are translated and integrated in the protein databank. Hence, by using BLASTX, a DNA query sequence is insert into the computer and six reading frames are translated that used for comparing in a protein databank. On the other hand, TBLASTN is used to compare a protein query to translated DNA sequences from the databank. Normally, BLASTP is used to compare protein sequence query to protein databank.
The computer is able to deal with a more complex scoring system based on a conditions of all the potential amino acid pairings. The scores in the matrix are used to calculate the overall score for the matching of amino acid, even though the sequence lining obtained merely mark matches above a selected cut-off score.
Dayhoff Point Accepted Mutation (PAM) matrices are derived from comparisons of related protein from distinct sources. The score is calculated from the numbers of time that the particular changes in amino acid sequence occur. It explains the similarity between the amino acids nevertheless is also affected by the nature of the genetic code. The Dayhoff PAM250 matrix is suitable for distantly related sequences, values of 0 refer to neutral changes, and increasing positive or negative values represent increasingly acceptable or unacceptable mutation respectively. A mismatch between phenylalamine (F) and tyrosine (Y) gives a greater score than a perfect match of all amino acids since F and Y match are quite rare and less possible occur by chance, so the score of 7 is given in the matrix.
An alternative of an amino acid within the same group can make a small influence on the structure and function of the protein, whereas a change of one amino acid between groups will make a greater effect to the protein.
While, the use of BLASTP as the default, an alternative family of matrices that known as BLOcks SUbstitution Matrix (BLOSUM), the numbering of the matrix title is totally different from the PAM matrices, it works in the opposite direction. BLOSUM is more appropriate for procedures based on local alignments.
3. Sequence Alignments
FASTA and BLAST only show pairwise alignments, instead of showing the ideal alignment between the search sequence and the target. Both are carry out rapidly and smaller amount of computer power. They make shortcuts to facilitate database searches.
The program Clustal includes ClustalW2 and Clustal X2, is used generally to produce optimized multiple alignment. They compared customize sequences to yield a matrix of pairwise alignment scores. Due to the similarity, two similar sequences are lining up together to generate new consensus until all the proteins in a multiple alignment had produced. Clustal alignments are same as Blast alignments, they concerned about the gap penalties and amino acid substitution matrices.
Furthermore, the substitutions of similar amino acids may influence the biological functionality of the protein. The alignment can be improve by introducing an extra gap into one of the sequences, rather than taking an alignment of sequences as an absolute, so as to aid towards the formation of evolutionary relationships. By identifying the sites of amino acids in the 3D structure of the proteins, we are able to distinguish whether alignment occurs in a region vital for the function of the protein.
Clustal is used to produce a phylogenetic tree based on the corresponding sequence of the proteins, and followed by Neighbour Joining to continue constructing the tree. The tree based on Clustal alignment is expected similar to the taxonomic relationships of the organisms.
Reference:
J. Dale and M. von Schantz, Plant N (2012). Sequencing a Cloned Gene. From: Genes to Genomes. Concepts and Applications of DNA Technology. Wiley Blackwell.

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