Sunday, December 28, 2014
දැනගැනීම පිණිසයි! ෆේස්බුක් සහ මම
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!
Wednesday, December 24, 2014
SAFEGUARD THE COMMUNICATION NETWORK SYSTEMS IN CASE OF EVENTS SUCH AS SEVERE SUN STORM
Roshan Karunarathna (rosh@vau.jfn.ac.lk)
1. INTRODUCTION
The sun’s magnetic and sunspot cycles have being expected to get peak from 2013, bringing a stormy season to our solar system and an increase in sun related damage here on Earth. - Power networks, pipelines, radio communications and the global positioning system (GPS) are all entering a period of increased risk of outages from geomagnetic storms as the solar activity cycle peaks in 2013.
Our sun is a massive ball of superheated gases that swirl with incredible currents and magnetic fields. At times the pressure builds up into sunspots, which can explode out from the sun in events known as solar flares, solar proton events (SPEs) and coronal mass ejections (CMEs).
2. IMPACT OF SOLAR STORMS
Solar events happen all the time, but 2013 was predicted to be a particularly bad year due to the peaking of several sun cycles. The last time this happened was in 1859 when the largest recorded solar storm spun compasses, disrupted telegraph service, and lit up the skies. Our dependency on electronics and an overloaded power grid makes us much more vulnerable to solar storms today.
“Solar storms” bombard the solar system – and Earth – with radiation and magnetic shock waves that can wreak havoc on magnetic fields, power systems, and electronics devices. The Earth’s atmosphere shields us from much of the radiation, but solar storms can still do quite a bit of damage, including:
• Short out satellites and take down GPS, cell phone, Internet, and TV services.
• Cause damage to electronic devices and computers.
• Disrupt the power grid resulting in overloads, widespread power outages, and dangerous power surges. • Increase corrosion and breakage of gas and fuel pipelines.
• Confuse compasses and electromagnetic gadgets.
• Cause light displays (like the “northern lights”) in the sky.
• Knock out communications, including radio, military communications, and early warning systems.
3. IMPACT OF SOLAR STORMS ON COMMUNICATION NETWORK
Solar storms can affect radio communications, satellite communications, radars and navigation systems. When consider about effect on communications, in the past solar storms have caused billions of dollars of commercial satellites to malfunction and die prematurely. A Great solar storm has the power to destroy many space assets (Space Station, Space Shuttle, LEO Satellites, GEO Satellites, and Off World Missions) simultaneously.
3.1 RADIO COMMUNICATION
On frequencies below 30MHz, the ionosphere generally acts as an efficient reflector, allowing communications to distance. Solar extreme ultraviolet and soft x-ray emissions from solar flares change the electron density and gradients in the ionosphere reflections. A sudden increase of x-ray radiation from a solar flare causes substantial ionization in the lower region of the ionosphere producing ionospheric disturbances of radio signals, sudden phase anomalies, sudden enhancement of signals and short wave fade. Solar flares also produce a wide spectrum of radio noise (Cohen N and et al., 1994).
Polar cap absorption (PCA), aurora absorption, multipatting and non-great circle propagation effects are associated with coronal mass ejections (CMEs) that can disrupt radio communications. The effects of solar storms on radio communications through ionospheric reflectivity and scintillation include (NSSA, 2007, Barnes, P.R and et al., 1991)
3.2 SATELITE COMMUNICATION
In our technology driven society, satellites play an important role in communications. The loss of satellites can affect: major news wire service feeds, network television, satellite Television and cable programming, nationwide radio service, weather data, cell phone service, pagers, automated teller machines, gas station credit card handling services, airline weather tracking services, earthquake monitoring network, blackberries, GPS navigation service, and critical military & airline communications. And this list grows longer every day.
Current commercial satellites are light-weight, sophisticated, built at the lowest cost using off-the- shelf electronics. This current low cost approach makes new satellite design more vulnerable to damage from solar storms due to less radiation hardening. A high-energy particle from an SPE can penetrate the wall of a satellite and deposit sufficient charge to cause an electrical upset to a circuit switch, false command, memory state change or loss. As the nuclear particles collide within the spacecraft, they release electrons that build up an internal dielectric charge. This static charge can destroy circuitry on electronic boards. The particles can also change data and instructions stored in computer memory. Some of the memory damage is soft causing Single Event Upset (SEU). Generally, this anomaly can be corrected by a computer reboot. But some of the damage can be hard causing unrepairable physical damage to the junction of the microcircuit. These types of failures can be fatal. Satellites receive their operating power from large solar panels arrays. High-energy protons from SPEs and CMEs can damage the solar cells by causing the silicon atoms in the solar cell matrix substrate to violently shift position which produce crystal defects. These defects increase the resistance of the solar cells to electrical current. As a direct result, solar cell efficiency steadily decreases and solar panel power drops off.
One critical satellite system that is very sensitive to damage from solar storms is the Attitude Control System. If the system is damaged or compromised, the satellite will become disoriented. Without accurate orientation data, the satellite will be unable to make fine adjustments to its orbit to prevent the satellite from reentering Earth’s atmosphere and burning up.
Another threat is differential charging. Charged particles striking different areas of a spacecraft can cause these sections of the spacecraft to be charged to different levels.
3.3 SUMMARIZED EFFECTS CONSIDERING DIFFERENT ASPECTS
• HF Radio Communication(3.3.MHz)
o Increased absorption.
o Depressed maximum usable
frequencies (MUF).
o Increased fading and flutter
o Effect short–wave propagation
through sunlit side of earth.
• VHF propagation (30 – 300MHz)
o Effect pagers and cellular phones
o Susceptibility to fadeout of the high and low band in mobile voice communications for
dispatching utility company line crews
• Satellite communications (200MHz to several GHz)
o Increased scattering of satellite- to-ground ultra-high frequency (UHF) transmissions or
scintillation can seriously interfere with direct satellite communications links
• Radio frequency interfere (RFI)
o Loss of phase lock
o Severe distortion of data
transmissions from
geosynchronous satellites
o Erroneous positioning information from single frequency GPS
o Drastic loss in spacecraft electrical power due to inability to reposition craft.
o Faraday rotation of the plane of polarization effect on satellites that employ linear polarization up to 1GHz
• Radar surveillance systems
o Azimuth angle errors
o Range errors
o Radar energy scatter due to
auroral interference
o Elevation angle errors
• Navigation systems
o position errors
o Scintillation of GPS signals
o Inaccuracy due to the
introduction of small delays
from GPS satellite signals
o fadeout of signals
4. PREVENTIVE MEASURES
Having analyzed the threats that can be caused by solar storms upon the improved technologies being enjoyed today, it is necessary to highlights measures to mitigate them. So protecting Network Communication systems is also got a vital importance due to the reason modern world is depend on such technologies mostly. These precautionary measures include but not exhaustive of the following:
o Use of series capacitors to block the flow of GIC in transmission lines or neutral – blocking capacitors in transformer neutrals.
o Putting sunscreen on all technology.
o Replacement of copper wires with optical fibers by telecommunications operators
o Installation of solar storm warning system (solar monitor) that can offer up to date information on solar activity, including images, flares locations, flare predictions.
o Use of shorter transmission cables as they are less vulnerable to damage.
o Long term preventive measures also exist to protect against coronal mass ejections, including digging transmission cables into the soil, placing lighting rods on transmission wires, reducing operating voltages of transformers and using cables that are shorter than 10 kilometers. It might also be possible to develop and deploy large resistors that would add another level of protection to large transformers.
o Incorporating solar storm hardening into satellite design.
o By receiving geomagnetic storm alerts and warning (e.g. by the space weather prediction center, via space weather satellites), power companies can minimize damage to power transmission equipment by momentarily disconnecting transformers or by inducing temporarily blackouts.
4.1 PREPARING FOR OUTAGES
The biggest threat of a solar super storm is a knockout of the power and communications grids that might take some time to repair. You can prepare for this the way you’d prepare for any kind of storm, by stocking up on:
Off the Grid Power: Buy a generator and extra fuel, or install a backup energy supply such as solar panels or a wind turbine.
Battery Backup for Computers: An Uninterrupted Power Supply (UPS) looks a lot like a standard surge protector but contains batteries that keep computers running smoothly without damage during power fluctuations and brownouts.
Emergency Supplies: Create an emergency box with flashlights, batteries, cooking and heating fuel, food, and clean water. Also, consider a backup stash with paper copies of financial and personal records, cash, road maps, address book, radio, first-aid kit, and anything else you’d need if your handy digital gizmos – along with your car, credit cards, bank, and shopping center – are out of commission for a while.
Figure 1.Portable generator |
Likewise, a powerful solar storm may cause major power surges that might fry anything in its path. Protect your electronics by using:
1. Whole House Surge Protector: A whole house surge protector connects to your breaker panel and provides protection from lightning and other power surges.
2. Individual Surge Protectors: For added protection, or in the absence of a whole house surge protector, install surge protectors on computers, TVs, stereos, and other electronics in your home.
Figure 2.Surge Protector |
5.1 "SOLAR SHIELD" COULD HELP KEEP”THE LIGHTS ON”TO HAVE A CONTINUE
POWER OVER DEVICES.
"Solar Shield is a new and experimental forecasting system”. We can zero in on specific transformers and predict which of them are going to be hit hardest by a space weather event. The troublemaker for power grids is the "GIC" – short for geomagnetically induced current. When a coronal mass ejection (a billion-ton solar storm cloud) hits Earth's magnetic field, the impact causes the field to shake and quiver
During extreme storms, engineers could safeguard the most endangered transformers by disconnecting them from the grid. That itself could cause a blackout, but only temporarily. Transformers protected in this way would be available again for normal operations when the storm is over. The innovation of Solar Shield is its ability to deliver transformer-level predictions.
How it works:
Solar Shield springs into action when we see a coronal mass ejection (CME) billowing away from
the sun. Images from SOHO and NASA's twin STEREO spacecraft shows the cloud from as many as three points of view, allowing to make a 3D model of the CME, and predict when it will arrive.
While the CME is crossing the sun-Earth divide, the Solar Shield team prepares to calculate ground currents. The crucial moment comes about 30 minutes before impact when the cloud sweeps past ACE, a spacecraft stationed 1.5 million km upstream from Earth. Sensors onboard ACE make in situ measurements of the CME's speed, density, and magnetic field. These data are transmitted to Earth and the waiting Solar Shield team.
Computer models predict fields and currents in Earth's upper atmosphere and propagate these currents down to the ground." With less than 30 minutes to go, Solar Shield can issue an alert to utilities with detailed information about GICs.
This idea of Solar Shield is experimental and has never been field-tested during a severe geomagnetic storm. A small number of utility companies have installed current monitors at key locations in the power grid to help the team check their predictions.
5.2 EARLY WARNING SYSTEM
Geomagnetic storms are triggered when a billion tones or more of solar plasma erupts from the surface of the sun at speeds of up to 3,000 kilometers per second, in what is known as a coronal mass ejection (CME).
If the mass ejection occurs in the direction of Earth, it can interact with the planet's own magnetic field and induce a substantial voltage on the surface. Long man-made conducting paths such as transmission lines, metallic pipelines, cables and railways act as antennae, focusing and transferring the current.
But CMEs are difficult to predict. They often batter Earth about four to five days after a solar flare is observed, but not always. The Advanced Composition Explorer (ACE) satellite, stationed a million miles from Earth, can detect the intensity of an incoming storm but may give as little as 30 minutes warning of its arrival. Forecasters issue a Sudden Impulse Warning, which indicates the Earth's magnetic field will soon be distorted by an incoming geomagnetic disturbance.
Demand for solar weather predictions and warnings has grown rapidly from operators of power, communications and navigation systems and airlines, but the crucial ACE satellite is aging and nearing the end of its useful life.
5.3 NETWORK SECURITY SYSTEM
5.3.1 USING POWER SURGE PROTECTORS
The devices should be protected with power surge protectors. After a situation, all grids have procedures for a "black start" following complete collapse: first by starting up specialist diesel generators, re-energizing selected power plants, connecting them to the grid, then gradually bringing the rest of the power generating sets back online and gradually restoring power to customer’s one area at a time. Less likely (but much more damaging) would be if a storm caused some of the extra-high voltage (EHV) transformers on the network to overheat and burn out. Most networks have only limited supplies of EHV transformer components, and there would be long lead-times for designing, manufacturing and installing new ones.
If a large number of transformers were fried, it might take months to restore power, according to a report on the "Effects of Geomagnetic Disturbances on the Bulk Power System" published by the North American Electric Reliability Corporation (NERC) in February 2012.
5.3.2 ACT WHEN TRANSMISSION IS IN HIGH DEMAND
Risks to the network and transformers are heightened when power lines and transformers are operating close to capacity. The biggest danger comes in spring and autumn, when a relatively small number of power plants are operating and transmission is in high demand. The simplest way to safeguard the network is to cut the demand for transmission, which lowers the operating temperature of the transformers so they have more room to rise safely without causing permanent damage. Grid operators can cut pressure on the network by increasing the amount of local generation (calling up more units from standby). In extreme cases, customers' power can be disconnected. Better a temporary loss of supply than one that lasts for months. Upgrading to newer and more reliable transformers can also harden the network against the risk of burn-out and failure.
Interest in space weather prediction is rising. The hope is that even a few minutes’ notice about an incoming storm at level G4 or G5 could allow networks to move to a safer operating mode or temporarily shut down as a precaution.
REFERENCES..
Web References…
1. http://www.space.com/713-space-storm-hits-earth-survives.html
2. http://www.solarstorms.org/SWChapter1.html
3. http://www.todayshomeowner.com/how-to-protect-your-home-from-solar-flares- and-solar-storms/
4. http://science.nasa.gov/science-news/science-at-nasa/2010/26oct_solarshield/
5. http://www.solar-facts-and-advice.com/coronal-mass.html
Papers….
1. Impacts of solar storms on energy and communications technologies
*Omatola, K.M. and Okeme, I.C.
Department of Physics, Kogi State University, Anyigba, Nigeria
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!
Monday, December 22, 2014
ඔයයි මමයි එක දවසක්........(1)
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!
Tuesday, December 16, 2014
මොකද්ද මේ JADE???
මේ තියෙන්නේ සයිට් එක |
ප්රධාන මුහුණත(main interface) |
අපි ඉදිරියට මේක පාවිච්චි කරන හැටි ගැන කතා කරමු.මේ ගැන මගේ දැනුමත් ටිකක් නෙවෙයි ගොඩක් අඩුයි ඒ නිසා වැරදි දේ තිබෙනවා නම් නිවැරදි කරන්න.මෙහෙම සිංහලෙන් ලියන්න හිතුවේ කැම්පස් එකේ මේ සබ්ජෙක්ට්ස් මුලින් පටන් ගන්න කොට ග්රීක් වගේ නිසා අපි මේ සම්බන්ධ සිද්දාන්ත සමග ජේඩ් ගෙන් වැඩ ගන්න එක ගැන කතා කරමු අදට ඇති නේද???
මේ වැඩසටහන පාවිච්චි කරන කොට |
මේ ගැන ලියවිලා තියෙන එයාලා නිර්දේශ කරන පොත මේක..මේ ලින්ක් එක මම වෙනත් සයිට් එකකින් තමා ගත්තේ.පුලුවන් අය ඉතින් පොත සල්ලි දීලා ගන්න එකයි ඇත්තේ ඔන්න අපි එහෙමනේ :පී!
මේ ප්රසන්ටේෂන් එකත් නියමයි බලන්න....
කෘතිම බුද්ධිය ගැන කතා කරන කොට මම සඳහන් කල යුතුම පොතක් තියෙනවා.මේ මේ සම්බන්ධව ලියැවුනු සරළම සහ හොදින්ම විස්තර තියෙන පොත කියලයි මම හිතන්නේ.මේ පොතේ කතන්දරයක් කියන විදිහට ඉතා හොදින්ම මේ සංකල්ප කියලා දෙනවා.මම මේක කියෙව්වේ උසස් පෙළ කරලා ඉවර වුනු ගමන් වගේ! ඒ නිසා මේක ඕන කෙනෙක්ට තේරුම් ගන්න පුලුවන් පොතක් කියන එක පැහැදිලියි! පොතේ නම තමයි “පින්කි“ ලියලා තියෙන්නේ මහාචාර්ය අශෝක එස් කරුණාරත්න මහත්මයා.පොතේ පින්තූර ටිකක් දාන්නම් කැමති අය හොයාගෙන කියවන්න.එක හුස්මට කියවන්න පුලුවන් මරු පොතක්!
A nice book about artificial intelligence from a Sri Lankan, describes main concepts of AI using a friendly story approach a book not to miss guys ................
written by Prof Asoka S Karunananda -The Dean, Faculty of Information Technology, Katubedda, Moratuwa Sri Lanka
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!
මයික්රෝසොෆ්ට් අණසක! (Microsoft SWAY) ඇප් එක....!
මයික්රෝසොෆ්ට් කියන විදිහට:
It’s been only 10 weeks since we kicked off Sway Preview, and we’ve already had over one million unique visitors to Sway.com and over 175,000 requests to join, and those numbers grow by thousands daily.SWAYයනු ගොඩක් දෙනෙක් ආස කරන නිෂ්පාදනයක් වෙයි ඊට හේතුව ඒක අර අපි දකින Microsoft Office මෘදුකාංගයේ ලිපිගොනු ආකෘතියෙන් මදක් බැහැරවෙලා කියෙන නිසා.මේ නිසා swayගොඩක් ම cloud එකට හදපු ඇප් එකක් කියන්න පුලුවනි.මේක අනික් අතට MS Office මෘදුකාංගය මේ cloud තාක්ෂනය හරහා ජනප්රිය කරවීමේ තවත් උත්සාහයක්.දැනටත් අපිට මේ පහසුකම තිබෙනවා මේ සඳහා ඔබට මයික්රෝසොෆ්ට් ගිණුමක්(Microsoft Account) තිබිය යුතුයි!එය නොමිලේ ඔබට නිර්මාණය කරගන්න පුළුවන්.අනාගතේ මේ ඇප් එකට කොච්චර පිරිසක් ආකර්ශනය වේවිද ජනප්රියතාවය කොහොම වෙයිද කියන්න අපි දන්නේ නෑ ඒත් දැනට හොද ප්රතිචාර තියෙන බව නම් පේනවා.මාත් ටිකක් පාවිච්චි කරලා බැලුවා මේ සබැඳුමෙන් මේකට ගිහින් බලන්න වැඩ ගොඩක් කල හැකියි!.
මෙහිදී ඔබ ගන්න කැන්වස් එහෙම නැත්නම් වැඩ කරන මුහුණත සාම්ප්රදායික ලිපි ගොනුවකට එහා ගිය දෙයක්!මෙක වෙබ් පිටු සඳහා හා අන්තර්ජාලයට එක් කිරීමට පහසු හා ගැලපෙන ලෙස ඔබේ ලිපිය සකසා දෙනවා.මීට අමතරව ඔනෑම උපාංගයකට(any device) සහය දක්වන ලෙස තමයි මේ නිර්මාණ ඔබ කරන්නේ.මේක ක්ලවුඩ් තාක්ෂනය සමත ක්රියාත්මක වන නිසා ඔයාට ඔයාගේ සමාජ වෙබ් අඩවි වලින් අන්තර්ජාලයෙන් අවශ්ය දේ කෙලින්ම ඔබේ නිර්මාණයට එක් කර ගන්න පුලුවන් කලින් කිව්වා වගේ ඒක ශෙයා කරන්නත් පහසුවෙන්ම පුලුවන්......
මේ තියෙන්නේ මේ ඇප් එක භාවිතා කරලා කරපු නිර්මාණයක්! මේක මම ගත්තේ මයික්රෝ සොෆ්ට් වෙබ් අඩවියෙන්මයි!
මේ තවත් එකක්
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!
Sunday, December 14, 2014
මේ ඔබේ උදව් අවශ්ය කාලයයි! රටට වැඩ ඇති දෙයකට දායක වෙමු.......
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!
Chou-Fasman Algorithm for Protein Structure Prediction
Chou-Fasman Algorithm for Protein Structure Prediction
1. INTRODUCTION
importance of protein structure in understanding the biological and chemical activities of organisms. Understanding about the proteins is important in various occasions such as finding cure for illnesses designing new chemical formulas and in studies on food and nutrition. The experimental methods used by biotechnologists to determine the structures of proteins demand sophisticated equipment and time. A host of c omputational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results. Chou-Fasman algorithm is an empirical algorithm developed for the prediction of protein secondary structure
1.1 Proteins
Examples of proteins:
a) Protective Proteins, for example, keratin (nails). b) Defence Proteins, for example, antibodies.
c) Toxins, for example, snake venom.
d) Structural Proteins, for example, collagen of bones. e) Enzymes (biocatalysts), for example, pepsin, trypsin. g) Hormones, for example, insulin is a protein.
1.2 Structure of Protein
-NH2
|
+
|
-COOH
|
=
|
-CONH-
|
Amino group
(Amino acid 1)
|
Carboxylic group
(Amino acid 2)
|
Peptide Bond
|
Amino acids are the basic building blocks of proteins. Fundamentally, amino acids are joined together by peptide bonds to form the basic structure of proteins.
Amino acids play central roles both as building blocks of proteins and as intermediates in metabolism. The 20 amino acids that are found within proteins convey a vast array of chemical versatility.
The chemical properties of the amino acids of proteins determine the biological activity of the protein. In addition, proteins contain within their amino acid sequences the necessary information to determine how that protein will fold into a three dimensional structure, and the stability of the resulting structure.
1.3 Amino Acids
Fig. 1 A generic Amino acid Structure |
Amino acids get together and form peptides or polypeptides. It is from these groupings that proteins are made. Commonly recognized amino acids include glutamine, glycine, phenylalanine, tryptophan, and valine. Three of
those phenylalanine, tryptophan, and valine are essential amino acids for humans; the others are isoleucine, leucine, lysine, methionine, and threonine.
Amino acids are carbon compounds that contain two functional groups: an amino group (NH2) and a carboxylic acid group (COOH). A side chain attached to the compound gives each amino acid a unique set of characteristics. It got another R part which may different for each amino acid.
2. INVESTIGATING THE PROTEIN STRUCTURE
Fig. 2 Different representations of protein structure |
• Primary Structure is the sequence of amino acids in the protein. Counting of residues always starts at the N- terminal end (NH2-group), which is the end where the amino group is involved in a peptide bond. The primary structure of a protein is determined by the gene corresponding to the protein.
• Secondary Structure is the composition of common patterns in the protein. Some patterns are frequently observed in the native states of proteins. This structure class includes regions in the protein of these patterns but it does not include the coordinates of residues.
• Tertiary Structure is the native state, or folded form, of a single protein chain. This form is also called the functional form. Tertiary structure of a protein includes the coordinates of its residues in three dimensional spaces. The elements of secondary structure are usually folded into a compact shape using a variety of loops and turns.
• Quaternary Structure is the structure of a protein complex. Some proteins form a large assembly to function. This form includes the position of the protein subunits of the assembly with respect to each other.
3. SECONDARY STRUCTURE PREDICTION
Given a protein sequence with amino acids a1, a2. . . an, the secondary structure prediction problem is to predict whether each amino acid ai is in a α−helix, a β−sheet, or neither. If we know (say through structural studies), the actual secondary structure for each amino acid, then the 3-state accuracy is the percent of residues for which our prediction matches reality. It is called “3-state” because each residue can be in one of 3 “states”: α, β, or other (O). Because there are only 3 states, random guessing would yield a 3-state accuracy of about 33% assuming that all structures are equally likely. There are different methods of prediction with various accuracies. Some of these methods are:3.1 GOR Method
The GOR method, named for the three scientists who developed it – Garnier, Osguthorpe,and Robson. Considering the information carried by a residue about its own secondary structure is used here, in combination with the information carried by other residues in a local window of eight residues on either side. Here the sequence of the residue concerned.The accuracy of these early methods based on the local amino acid composition of single sequences was fairly low, with often less than 60% of residues being produced in the correct secondary structure state.
3.2 PHD
The neural net model employed by Rost and Sander was fairly complex and computationally expensive. Because of the computational demands, a 7-fold cross-validation was used in place of jack-knife testing. Accuracy was over
70% using multiple sequence alignment, but the fifth of residues with the highest reliability was predicted with over
90% accuracy. Rost and Sander also tested PHD on 26 new proteins, none with significant sequence similarity to any protein in the training set, and found comparable results. PHD, however, suffers from some problems. Rost and Sander were concerned with overtraining and therefore terminated training once the accuracy was higher than 70% for all training samples.
3.2 Chou- Fasman Method
The Chou-Fasman method was among the first secondary structure prediction algorithms developed and relies predominantly on probability parameters determined from relative frequencies of each amino acid's appearance in each type of secondary structure. In this method, a helix is predicted if, in a run of six residues, four are helix favouring and the average valued of the helix propensity is greater than100 and greater than the average strand propensity. Such a helix is extended along the sequence until a proline is encountered (helix breaker) or a run of 4 residues with helical propensity less than 100 is found. A strand is predicted if, in a run of 5 residues, three are strand favouring, and the average value of the strand propensity is greater than 1.04 and greater than the average helix propensity. Such a strand is extended along the sequence until a run of 4 residues with strand propensity less than 100 is found.
3.3 Data Mining Model used for implementation of the CHOU- FASMAN method
As a part of the larger process known as knowledge discovery, data mining is the process of extracting information from large volumes of data. This is achieved through the identification and analysis of relationships and trends within commercial databases. Data mining is used in areas as diverse as space exploration and medical research. Here we gather data considering the known protein structures. The predictions are concerned with the data we already have. We compare the particular values of the protein we want to predict the structure and thus do the prediction on its structure
4. CHOU-FASMAN METHOD FOR PROTEIN STRUCTURE PREDICTION
The Chou-Fasman algorithm for the prediction of protein secondary structure is one of the most widely used predictive schemes. The Chou-Fasman method of secondary structure prediction depends on assigning a set of prediction values to a residue and then applying a simple algorithm to the conformational parameters and positional frequencies. The Chou-Fasman algorithm is simple in principle.The conformational parameters for each amino acid were calculated by considering the relative frequency of a given amino acid within a protein, its occurrence in a given type of secondary structure, and the fraction of residues occurring in that type of structure. These parameters are measures of a given amino acid's propensity (preference to be found in helix, sheet or coil). Using these conformational parameters, one finds nucleation sites within the sequence and extends them until a stretch of amino acids is encountered that is not disposed to occur in that type of structure or until a stretch is encountered that has a greater disposition for another type of structure. At that point, the structure is terminated. This process is repeated throughout the sequence until the entire sequence is predicted.
4.1 Propensity value
To predict secondary structure of a protein using Chou-Fasman method from a primary sequence require the knowledge of propensity value. Simply propensity value is the tendency of an amino acid to be present in α-helix or β –sheet. Suppose an amino acid which is having a higher propensity value for α (P(α)).That means that amino acid is alerted to be present in α-helix more than it is to be present in β-sheets. Similarly in the case of β-sheets also. Propensity value is depicted as P. So the propensity value for β will be Pβlikewise.4.2 Calculation of the propensity value
4.3.1 α-Helix/ β -Sheets Nucleation
It is regarding the tendency to make helixes/sheets in our amino acids.it depends on how many α-helix / β-sheet makers and α-helix/ β-sheet breakers in the amino acid sequence we study. Normally an amino acid becomes a breaker or a maker because of the R part it got. According to the R part in the Amino acid it isdetermined whether the particular amino acid is mostly in α-helix or β -sheet. So we use this concept to determine the secondary structure in Chou-Fasman Method.
The concept is for α-helix is:
More than 1/3 (>1/3 in this case 2) of α-helix breakers it should not form an α-helix.
1>
4.3.2 α-Helix/ β -Sheets Termination
This is about the calculating the ending point of a α--helix or a β -sheet in the sequence here also we consider randomly a contiguous 6 residues and we apply the above rule and then consider this for the both
directions from our selected residues set adding one amino acid for a once and when we get 4 times residues having their propensity value less than 100 we can say that our structure end its α-helix from here or end its β - sheet from here and we check for a new sequence.
4.3.3 α-Helix/ β -Sheets overlapping comparison
When the particular sequence having both α-helix and β -sheets we need to determined which will it get
the most this is decided using the Pa and P β values if Pa is high we say its alpha if P β is high it in β .
So the conditions we check in this method are
H α<>B α
P α<1 .03="" br="" or="" p="">P α<>P β
and if we found four consecutives with Pα or P β less than 100 we say this segment is end from here and it gets this structure(may be α or β or may be not both???)
4.4The Algorithm
The Chou-Fasman method of secondary structure prediction depends on assigning a set of prediction values to a residue and then applying a simple algorithm to those numbers.
The algorithm contains the following steps:
(a) Assign parameter values to all residues of the Peptide.
(b) Scan the peptide and identify regions where 4 out of 6 contiguous residues have P(α)>100.Theseregions nucleate α- helices. Extend these in both directions until a set of four contiguous residues have an average P(α)<100 .this="" br="" ends="" helix.="" the="">
(c) Scan the peptide and identify regions where 3 out of 5 contiguous residues have P(β)>100.These residues nucleate β- strands. Extend these in both directions until a set of four contiguous residues have an average P(β)<100 .this="" br="" ends="" strand.="">
(d) Any region containing overlapping α and β assignments are taken to be helical or β depending on if the average P(α) and P(β) for that region is largest. If this residues an α or β- region so that it becomes less than 5 residues, the α or β assignment for that region is removed.
(e) To identify a β-turn at residue number i, the product p(t) = f(i)f(i+1)f(i+2)f(i+3) is calculated. To predict a β- turn, the following three conditions have to be simultaneously fulfilled:
p (t)>0.000075
p(t) = f(i)f(i+1)f(i+2)f(i+3) .
Where the f(i+1) value for the i+1 residue is used, the f(i+2) value for the i+2 residue is used and the f(i+3) value for the i+3 residue is used
• The average value for P (turn)>100 for four amino acids.
• The average P (turn) is larger than the average P (α) as well as P(β).
(f) The remaining part of the sequence without Assignment = are considered as coils.
Α-HELIX, ß-SHEET AND TURN RESIDUES.
Name
|
P(a)
|
P(b)
|
P(turn)
|
f(i)
|
f(i+1)
|
f(i+2)
|
f(i+3)
|
A-Alanine
|
142
|
83
|
66
|
0.060
|
0.076
|
0.035
|
0.058
|
R-Arginine
|
98
|
93
|
95
|
0.070
|
0.106
|
0.099
|
0.085
|
N-Asparticacid
|
101
|
54
|
146
|
0.147
|
0.110
|
0.179
|
0.081
|
D-Asparagine
|
67
|
89
|
156
|
0.161
|
0.083
|
0.191
|
0.091
|
C-Cysteine
|
70
|
119
|
119
|
0.149
|
0.050
|
0.117
|
0.128
|
E-Glumaticacid
|
151
|
37
|
74
|
0.056
|
0.060
|
0.077
|
0.064
|
Q-Glutamine
|
111
|
110
|
98
|
0.074
|
0.098
|
0.037
|
0.098
|
G-Glycine
|
57
|
75
|
156
|
0.102
|
0.085
|
0.190
|
0.152
|
H-Histidine
|
100
|
87
|
95
|
0.140
|
0.047
|
0.093
|
0.054
|
I-Isoleucine
|
108
|
160
|
47
|
0.043
|
0.034
|
0.013
|
0.056
|
L-Leucine
|
121
|
130
|
59
|
0.061
|
0.025
|
0.036
|
0.070
|
K-Lysine
|
114
|
74
|
101
|
0.055
|
0.115
|
0.072
|
0.095
|
M-Methionine
|
145
|
105
|
60
|
0.068
|
0.082
|
0.014
|
0.055
|
F-Phenylalanin e
|
113
|
138
|
60
|
0.059
|
0.041
|
0.065
|
0.065
|
P-Proline
|
57
|
55
|
152
|
0.102
|
0.301
|
0.034
|
0.068
|
S-Serine
|
77
|
75
|
143
|
0.120
|
0.139
|
0.125
|
0.106
|
T-Threonine
|
83
|
119
|
96
|
0.086
|
0.108
|
0.065
|
0.079
|
W-Tryptophan
|
108
|
137
|
96
|
0.077
|
0.013
|
0.064
|
0.167
|
Y-Tyrosine
|
69
|
147
|
114
|
0.082
|
0.065
|
0.114
|
0.125
|
V-Valine
|
106
|
170
|
50
|
0.062
|
0.048
|
0.028
|
0.053
|
4.4 Choice of sequence format
There are various formats of Amino acid sequences, and each has its own set of characters and utility. To get a deeper understanding and better results it is essential to choose a valid input format. The various formats are:• Plain text format
• FASTA format
• Genetic Computer Group Format (GCG)
• NEXUS
• NBRF &PIR
Ex:-Plain text format:
Plain Text format looks like the following:
MAYPMQLGFQDATSPIMEELLHFHDHTLMIVFLISSLVLYIISLMLTTKLTH TSTMDAQEVETIWTILPAIILILIALPSLRILYMMDEINNPSTVKTMGHQWY WSYEYTDYEDLSFDSYMIPTSELKPGELRLLEVDNRVVLPMEAAQQEEEE MAYPMQLGFQDATSPIMEELLHFHDHTLMIVFLISSLVLYIISLMLTTKLTH TSTMDAQEVETIWTILPAIILILIALPSL RILYMMDEINNPSTVKTMGHQWY WSYEYTDYEDLSF DSYMIPTSELKPGELRLLEVDNRVVLPMEAAQQE.
5 RESULTS AND DISCUSSION
For a given sequence of amino acids, this technique first clusters the amino acids and then these amino acid clusters are analyzed to predict the structure of protein. The user inputs the primary structure of the protein i.e. The amino acid sequence. The clusters of amino acids are extended till a alpha-helix, beta helix or a turn are predicted using the conformational parameters and positional frequencies for α- helix, ß-sheet and turn residues.
The whole detailed method is explained below: Example:
INPQAIFDIQIKRLHEYKRQHHDKQVHMANLCVVGGFA VNGVAALHSDLVVKDLFPEYHQLWPNKFHNVTNGITP RRWIKQCNPALAALLDKSLQKEWANDLDQLINLVKLA DDAKFRQLYRVIKQANKVRLAEFVKVRTIDLNLLHILA LYKERIRENP
The above sequence is divided into clusters and from the table the conformational parameter and positional frequencies for α-helix, ß-sheet and turn residues are established.
Ex:-for first 6, the pα>100 so it may not be in α- helix and the P ß >100 so it may not be either in ß-sheet, and then we consider it for turns and we can consider the structure to be in turns. And to determine the end points we choose random from the sequence and do the algorithm for both sides until we meet the breaking criteria.so following is the Output after considering structure
Hence the final secondary structure of the given sequence is:
TTTBBBBBBBBBBBBBTTTTAAAAAAABBBBBBBTTTTTTTTTTTTTTTTTTTTTBBBBBTTAA AAAAAAAAAAAAAAATTBBBBBBTTTTTTTTTTTTBBBBBBTTTTAAAAAAAATTTTTTTTB BBBTTTT
6 RESULTS AND DISCUSSION
It attempts to classify amino acid in protein sequence according to their predicted local structure, which can be subdivided into three states: α-helix, β-sheet or turn.
• Protein fold can be predicted with better accuracy with this technique.
• Various other data mining techniques can be used to determine an optimum result.
• Choice of various formats of amino acid sequences can be utilized.
• Protein structure and protein function prediction can be done based on improved Chou-Fasman method which includes 4 amino acids enabling a reverse β- turn.
7 FUTURE SCOPE OF WORK
There are lot of researches going on still regarding the improvements of the Chou-Fasman algorithm and there are several modified algorithms can be found when we search.
Following improvements regarding the developed model of bioinformatics can be made:
• The system can be extended to predict the tertiary structure of the protein.
• Various different mining techniques can be utilized to determine the optimum result.
• Different formats of amino acids can be utilized.
• Protein fold can be predicted with better accuracy with using this technique.
• This technique can be further extended for multiple sequence alignment.
8 REFERENCES
[1] András Fiser, Andrej Sali (2000) “Comparative protein structure modeling” Pels Family Center for Biochemistry and Structural Biology,The Rockefeller University, pp 82-88.[2] Andreas Rechtsteiner, Jeremy Luinstra, Luis M Rocha, Charlie E M Strauss (2006) “Use of Text Mining for Protein Structure Prediction and Functional Annotation in Lack of Sequence Homology” Center of Genomics and Bioinformatics, Indiana University, Bloomington, IN 47401, pp 1-4.
[3] Ben Blum, Michael I. Jordan (2007) “Feature Selection Methods for Improving Protein Structure Prediction with Rosetta” Department of Electrical Engineering and Computer Science University of California at Berkeley, CA 94305, pp1-7.
[4] Chen Yonghui, Reilly Kevin D., Sprague Alan P., Guan Zhijie, “SEQOPTICS: a protein sequence clustering system” Symposium of Computations in Bioinformatics and Bioscience (SCBB06) in conjunction with the International Multi-Symposiums on Computer and Computational Sciences 2006 (IMSCCS|06) Hangzhou, China. June 20–24, 2006, pp 1-5.
[5] Eisen Michael B., Spellman Paul T., Brown Patrick O., Botstein David (1998) “Cluster analysis and display of genome-wide expression patterns” Proc. Natl. Acad. Sci. USA.Vol. 95, pp.14863–14868.
[6] Fraley Chris, Raftery Adrian E. (1998) “How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis” The computer journal, Vol. 41, No. 8, 1998 pp 578-587.
[7] DSVGK Kaladhar (2012) “protein secondary structure prediction:an application of chou-fasman algorithmin a hypothetical protein of sars virus” Int. J. LifeSc. Bt & Pharm. Res.Vol.1, Issue. 1, January 2012pp 1-3.
[8] Fraley Chris, Raftery Adrian E. (2000) “Model based clustering, Discriminant Analysis, and density estimation” Working Paper no II, Center for statics and social science, University of Washington, USA, pp1-28.
[9] George Tzanis, Christos Berberidis, and Ioannis Vlahavas (2002) “Biological Data Mining” Department of Informatics, Aristotle University of Thessaloniki, Greece, pp 1-8.
100>100>1>
Roshan is an undergarduate student in Information and Communication Technologies from Vavuniya Campus of the University of Jaffna.He is very much interesting on IT related Topics and the technical stuffs.Roshan is also a creative mind with lots of ideas and potential writter..!