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Welcome to The Visible Embryo, a comprehensive educational resource on human development from conception to birth.

The Visible Embryo provides visual references for changes in fetal development throughout pregnancy and can be navigated via fetal development or maternal changes.

The National Institutes of Child Health and Human Development awarded Phase I and Phase II Small Business Innovative Research Grants to develop The Visible Embryo. Initally designed to evaluate the internet as a teaching tool for first year medical students, The Visible Embryo is linked to over 600 educational institutions and is viewed by more than ' million visitors each month.

WHO International Clinical Trials Registry Platform
The World Health Organization (WHO) has created a new Web site to help researchers, doctors and patients obtain reliable information on high-quality clinical trials. Now you can go to one website and search all registers to identify clinical trial research underway around the world!




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Pregnancy Timeline by SemestersFemale Reproductive SystemFertilizationThe Appearance of SomitesFirst TrimesterSecond TrimesterThird TrimesterFetal liver is producing blood cellsHead may position into pelvisBrain convolutions beginFull TermWhite fat begins to be madeWhite fat begins to be madeHead may position into pelvisImmune system beginningImmune system beginningPeriod of rapid brain growthBrain convolutions beginLungs begin to produce surfactantSensory brain waves begin to activateSensory brain waves begin to activateInner Ear Bones HardenBone marrow starts making blood cellsBone marrow starts making blood cellsBrown fat surrounds lymphatic systemFetal sexual organs visibleFinger and toe prints appearFinger and toe prints appearHeartbeat can be detectedHeartbeat can be detectedBasic Brain Structure in PlaceThe Appearance of SomitesFirst Detectable Brain WavesA Four Chambered HeartBeginning Cerebral HemispheresEnd of Embryonic PeriodEnd of Embryonic PeriodFirst Thin Layer of Skin AppearsThird TrimesterDevelopmental Timeline
Click weeks 0 - 40 and follow fetal growth
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July 12, 2012--------News Archive Return to: News Alerts

Graphic: Christine Daniloff.

WHO Child Growth Charts


Searching Genomic Data Faster

Biologists' capacity for generating genomic data is increasing more rapidly than computing power - A new algorithm will help them keep up

by Larry Hardesty, MIT News Office

Since 2002, the rate at which genomes can be sequenced has been doubling every four months or so, whereas computing power doubles only every 18 months. Without the advent of new analytic tools, biologists' ability to generate genomic data will soon outstrip their ability to do anything useful with it.

In 2001, the Human Genome Project and
Celera Genomics announced that after 10 years
and at a cost of some $400 million,
they had completed a draft sequence
of the human genome.

Today, sequencing a human genome
is something that a single researcher can do
in a couple of weeks for less than $10,000.

In the latest issue of Nature Biotechnology, MIT and Harvard University researchers describe a new algorithm that drastically reduces the time it takes to find a particular gene sequence in a database of genomes. Moreover, the more genomes it's searching, the greater the speedup it affords, so its advantages will only compound as more data is generated.

In some sense, this is a data-compression algorithm — like the one that allows computer users to compress data files into smaller zip files. "You have all this data, and clearly, if you want to store it, what people would naturally do is compress it," says Bonnie Berger, a professor of applied math and computer science at MIT and senior author on the paper.

"The problem is that eventually you have to look at it, so you have to decompress it to look at it. But our insight is that if you compress the data in the right way, then you can do your analysis directly on the compressed data. And that increases the speed while maintaining the accuracy of the analyses."

Exploiting redundancy

The researchers' compression scheme exploits the fact that evolution is stingy with good designs. There's a great deal of overlap in the genomes of closely related species, and some overlap even in the genomes of distantly related species: That's why experiments performed on yeast cells can tell us something about human drug reactions.

Berger; her former grad student Michael Baym PhD '09, who's now a visiting scholar in the MIT math department and a postdoc in systems biology at Harvard Medical School; and her current grad student Po-Ru Loh developed a way to mathematically represent the genomes of different species — or of different individuals within a species — such that the overlapping data is stored only once. A search of multiple genomes can thus concentrate on their differences, saving time.

Baym explains: "If I want to run a computation on my genome, it takes a certain amount of time. If I then want to run the same computation on your genome, the fact that we're so similar means that I've already done most of the work."

In experiments on a database of 36 yeast genomes, the researchers compared their algorithm to one called BLAST, for Basic Local Alignment Search Tool, one of the most commonly used genomic-search algorithms in biology. In a search for a particular genetic sequence in only 10 of the yeast genomes, the new algorithm was twice as fast as BLAST; but in a search of all 36 genomes, it was four times as fast. That discrepancy will only increase as genomic databases grow larger, Berger explains.


The new algorithm would be useful in any application where the central question is, as Baym puts it: "I have a sequence; what is it similar to?"

Identifying microbes is one example. The new algorithm could help clinicians determine causes of infections, or it could help biologists characterize "microbiomes," collections of microbes found in animal tissue or particular microenvironments; variations in the human microbiome have been implicated in a range of medical conditions.

It could be used to characterize the microbes in particularly fertile or infertile soil, and it could even be used in forensics, to determine the geographical origins of physical evidence by its microbial signatures.

Berger's group is currently working to extend the technique to information on proteins and RNA sequences, where it could pay even bigger dividends.

Now that the human genome has been mapped,
the major questions in biology are
what genes are active when,
and how the proteins they code for interact.
Searches of large databases of biological information
are crucial to answering both questions.

Original article: http://web.mit.edu/newsoffice/2012/genetic-searching-algorithm-0710.html