- The following is a brief list of facts regarding the human genome. .
The human genome is the complete list of coded instructions needed to make a human.
The human genome is composed of more than 3 billion nucleotide bases. There are 4 types of nucleotide base: A- adenine, T- thymine, C- cytosine, G- guanine.
The order of the nucleotide bases contains the instructions for making an organism. Every three bases codes for an amino acid.
There are 20 different amino acids that combined in different ways make different proteins.
The total number of human genes is estimated to be between 30,000 - 40,000.
Worms have 19,098 genes, fruit flies have 13,602 and yeast has 6,034.
Almost all nucleotide bases (99.9%) are exactly the same in all people.
Less than 2% of the genome codes for proteins.
The vast majority of the DNA in the genome (>97%) has no known function.
The functions remain unknown for over 50% of discovered genes.
Chromosome 1 has the most genes (2,968) and chromosome Y has the least (231).
Humans have about 3 times as many proteins as flies and worms. This is because different proteins can be produced by the same gene using the processes of mRNA splicing and protein post-translational modifications.
Our DNA is 98% identical to chimpanzees. The average amount of genetic difference between any 2 chimpanzees is 4 or 5 times more than the average difference between any 2 humans.
There are 100 trillion cells in your body.
If unwound and tied together, the strands of DNA in one cell would stretch 6 feet.
If all the DNA in your body was tied together, it would stretch to the sun and back over 600 times.
12,000 letters of DNA are decoded by human genome project computers every second.
The entire human genome requires more than 3 gigabytes of computer storage space.
If a person recited the genome at a rate of one nucleotide per second, 24 hours a day, it would take them a full century to complete.
To sequence the human genome, researchers collected a large number of blood samples from females and sperm from males. A few of these samples were then chosen at random for sequencing. The identities of the sample sources have never been disclosed, either to the donors or to the scientists.
Saturday, December 24, 2005
Human genome facts
ChandraMukhi --- Reloaded ( Part X )
Part X – Rajini’s – the mission possible
Rajini : As usual came to office late
Rajini : As usual came to office late
Prabhu : was in high tension …..
Rajini : what happened Prabhu ?? why are you so tensed ??
Prabhu : Jyo dint return home yesterday.. Called all her friends.. But I could not trace her ..
Rajini : What do you say ??? I was here till 2 o clock .. I dint notice anyone working here
Prabhu : I am having headache .. Let me go and sleep at home. If I get any important call make a call to me
Rajini : OK Prabhu
Rajini went out for a break and say Jyo entering office at 2.
Rajini : hey jyo … why are you so late to office ???
Jyo : I was working in the office till today morning 2 . was very tired and was afraid to drive my car. So I stayed with my school friend’s flat.
Rajini : Prabhu called your mobile it seems .. But you dint pick up ??
Jyo : Mobile was in silent mode …
Rajini and jyo enters office and they work their tasks
During tea break
Rajini : hey jyo .. You havnt completed the tasks assigned to you it seems ??
Jyo : ME !!! Jyo ‘s eyes as it turned devilish for a moment and then returned to normal..
Rajini : Cool Jyo … you have completed your task …. Come lets go and see that Chandralekha’s system
Jyo : What ??? that system .. No .. I cant come .. I am very afraid .. already some are saying tat we are losing all the files cos of that. And I have once entered the room . It was really very dark. I was scared to enter and came back .. some say even they hear some sounds during night
Rajini : Even I heard the sounds when I was working alone !! ( Jyo was really surprised to hear the same from rajini )
Rajini and Jyo enters the room and Jyo was so happy to say that this was Chandralekha’ system and the system was dust free.
Without Jyo’s notice Rajini was about to login to the system and happened to see Jyo’s id in it ..
Rajini : Jyo come on .. very sultry here .. let us go !!
Jyo : Rajini I m very tired and I m going home today
Rajini : Ok Jyo.. Good night and sweet dreams …
The Climax :
Rajini : Was in that dark room … He logged on to the system of Chandralekha and when he logged in was able to see lots of games and songs in her system and was able to see lots of codes which can be used in the project .
( thinks to himself … wat an intellectual gal … IT world has missed such a talented person .. )
As Rajini was playing a song … he was able to see disturbance in the network and the access was cut in few minutes … He connected his laptop and was having the same in the same room … he was able to see all those …
When rajini shut down the system .. The network was up .. So Rajini concluded that the probs was due to this system.
Then Rajini tried to transfer some of the codes from the system to his laptop … While the transfer was about to complete his entire softwares was hacked and was attacked by virus and his computer got hanged !!
Rajin found that each time Jyo tried to transfer some of the code snippets we had the crash and I was having network breakdown at nights.
Rajini started to think very deeply and found a solution …
We all hear this music as BGM !!
Come on, Come on
Yeah Come on,
Hey Come on, Come on…… , Yo!!!!!
I am back to explore, Give the comp, give a few minutes now,
S.A (System admin) thatz what they say
C to the C to the N to the A
S.A thatz what they say…
Rajini planned a software such that when ever some one tries to transfer softwares or games or music files from Chandralekha’s system he programmed a code such that it plays a song ( Bhakthi song ) such that the when the song played the blackmagic from the Chandralekha system becomes inactive and loses its power to reach the other system.
Rajini deployed this concept successfully and was able to put off the system back to the same place and happily comes out of the room with a victorious smile…
The end !!
Tuesday, December 20, 2005
Bioinformatics and drug discovery 2
Sometimes we want to develop broad spectrum drugs that are effective against a wide range of pathogenic species while at other times we want to develop narrow spectrum drugs that are highly specific to a particular organism. Comparative genomics helps to find protein families that are widely taxonomically dispersed and those that are unique to a particular organism.For example, when we want to develop a broad spectrum antibiotic, we are looking for targets that are present in a large number of bacteria yet have no similar homologues in human. This means that the antibiotic will be effective against many bacteria killing them while causing no harm to the human.
In order to determine the role our potential drug target plays in a particular disease mechanism we use DNA and protein chips. These chips can measure the amount of transcript or protein expressed by a cell at different times or in different states (healthy versus diseased). Clustering algorithms are used to organise this expression data into different biologically relevant clusters. We can then compare the expression profiles from the diseased and healthy cells to help us understand the role our gene or protein plays in a disease process.
All of these computational tools can help to compose a detailed picture about a protein family, its involvement in a disease process and its potential as a possible drug target. Following on from the genomics explosion and the huge increase in the number of potential drug targets, there has been a move from the classical linear approach of drug discovery to a non linear and high throughput approach. The field of bioinformatics has become a major part of the drug discovery pipeline playing a key role for validating drug targets. By integrating data from many inter-related yet heterogeneous resources, bioinformatics can help in our understanding of complex biological processes and help improve drug discovery.
In order to determine the role our potential drug target plays in a particular disease mechanism we use DNA and protein chips. These chips can measure the amount of transcript or protein expressed by a cell at different times or in different states (healthy versus diseased). Clustering algorithms are used to organise this expression data into different biologically relevant clusters. We can then compare the expression profiles from the diseased and healthy cells to help us understand the role our gene or protein plays in a disease process.
All of these computational tools can help to compose a detailed picture about a protein family, its involvement in a disease process and its potential as a possible drug target. Following on from the genomics explosion and the huge increase in the number of potential drug targets, there has been a move from the classical linear approach of drug discovery to a non linear and high throughput approach. The field of bioinformatics has become a major part of the drug discovery pipeline playing a key role for validating drug targets. By integrating data from many inter-related yet heterogeneous resources, bioinformatics can help in our understanding of complex biological processes and help improve drug discovery.
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