Showing posts with label bioinfo research. Show all posts

5:28 AM

From Start To Finish

Your PhD is going to be the focus of your professional and personal life for at least four years, so it is important that it will be time well spent. Here are some tips and points to consider to make sure you are a successful PhD student fromThe Graduate Recruitment Bureau.
So how do you get from start to finish and what can help keep you motivated throughout?

1)     Choose The Right University

*Research ahead of time which Universities express/match up with your best research interests and goals. Dig deeper as to what programs are ideal (look at alumni placement ratings-where do they end up? what percentage go in what sectors?), who has available funding, which programs offer stipends (is being a TA a requirement?), if there are training grants you should apply for (i.e. NSFor NIH), and which professors are looking to take students. With the NIH sequester in play, you’d be surprised how competitive things (positions as a result of funding) are becoming.
*Chances are if you email these professors ahead of time, you can meet with them prior to the start of your graduate program and beat out the crowd for limited lab slots available for grad students. The early bird gets the worm, as some graduate students even start working prior to the official start of the semester.
Financial backing is important, as your PhD can’t begin without it, so a major step for being a successful PhD student is to get financial funding, and as much of it as possible. PhDs are not cheap with all the material, equipment and research that is required. So, the more  secure financial aid you apply for, the less you need to worry about (if the financial aid is required and is graduate program dependent).
If funding is of concern, get in contact with any relevant business or organization(s) that might be interested in your research and willing to fund it for you. For example, research charities or councils that have shown a keen interest in your area of study fund doctorates and academic institutions will have lists of the PhDs they offer.
*Many life science programs give you a stipend to support you (and you might have to TA on the side). When that is not enough, check out 7 easy ways to earn an alternative income here: http://thegradstudentway.com/blog/?p=86

2)    Keep The Passion

An undeniable necessity for being a successful PhD student is to have a real passion for your topic. Your PhD will be your life for the next 4 or more years, so you need to be really committed to the subject with no risk of finding it tiresome.
The passion you feel for your subject will be tested throughout the course of your research due to work, time and supervisor pressures, so the bond you share needs to be indestructible. If you aren’t 100% committed to your topic, then you can’t put in the needed effort and passion that are key ingredients for a successful PhD. So, make sure you are really interested in the research you are about to undertake.

3)     Learn

Knowing the experts in your field can only help you and your PhD be a success. Apply to work with a prestigious tutor/mentor, as after all, who better to be your mentor than the leading expert in your field? If you don’t ask you don’t get so don’t be afraid to try.
In addition to having a tutor/mentor who seriously knows their stuff, you need to read, watch and listen to your favorite authors and researchers and then try and make contact with them. More often than not they will be more than happy to spend some time discussing their latest findings and theories with you- they are the Hollywood Royalty of academia so let the know you are their number one fan. You never know, they might have some life changing opportunities for you.

4) Network

Your PhD is going to take up a substantial part of your life, and it is important to realize that a successful PhD student will change their priorities from year to year. In the first year, you need to network and get your name out there and be known. If people don’t know you exist, how will they know about your research and whether it is something really ground-breaking that they should take an active interest in?
After your PhD, you are going to need contacts and opportunities and your research is the key to open all these doors, so take the time in the first year to spread your word and get involved in projects. In the final years, your main priority should be your work, so it is sensible to turn down some event invitations- you should have made a big enough fuss about yourself in the first year to be able to not attend some events and still not be forgotten. Build yourself a solid basis and name early on, and then complete your work knowing that the interest and knowledge about it is still out there.

5) Read

Doing a PhD means making an original contribution to the field; one of great value, interest and benefit. Your research needs to complement existing researchand not replicate anything.

Therefore, you need to read as much as possible including every piece of theory and research that has ever been done in your area. Know what has been found, what hasn’t been proved, what’s been suggested, successful and ignored. If you don’t know what is already in existence, then you can’t make an original and reputable contribution to the field. Therefore, it is essential that in order to be a successful PhD student that you start hitting those books.

6)     Communicate

It’s great that you’re doing all this research and discovering all these fascinating trends, but if you cannot communicate your research and progress effectively-then the real potential of your PhD will be lost.
Brush up on your communication skills. Your written communication needs to be impeccable; logically ordered, easy to follow and with a clear message. Obviously, grammatically correct and with no spelling errors too! When presenting your work to audiences at conferences and meetings it needs to be an exciting, engaging delivery.
Additionally, make sure you are presenting your work to the right people. To be a successful PhD student you need to be more than a great researcher; you need to be able to convey your findings and theories to a specialist audience in a way that will create and retain your professional, reputable image. This means no stuttering, no monotonous lengthy speeches and no waffling, unpunctuated sentences.

7)     Work hard

A good work ethic is pivotal to your PhD success. You need to work hard and play hard to stay motivated and sane during your PhD. It is essential that you allow yourself breaks if you feel as though it’s all getting too much and a touch of cabin fever is setting in. An hour’s break or a day off can do your research the world of good. If by lunchtime you are going mad then go for a jog, do some painting, bake a cake- whatever you do to reconnect and re-establish control. On the other hand you can’t take too many breaks, so keep in mind that you still need to stay productive.
Treat your PhD like a job- as it essentially is- which equates to five days a week and having down-time on weekends. Or, if you need to work weekends then make sure you allow yourself some relaxation in the week. The balancing act of work and play is a fine art, but master it and you’ll be a successful PhD student.

8)     Persevere

Perseverance is the key to success with all PhDs, as most research won’t instantly fall nicely into place right from the get-go. You need to stick with it and constantly reassess and modify your method(s) to achieve the best you can and derive promising results.
This means you must be organized as well as tenacious. Keep meticulously detailed notes at every stage of your work so far and have a plan of action so you always know what the next stage is. It doesn’t matter if in reality the next stage doesn’t pan out as planned, but by knowing which direction it is headed will help to channel your energy and research to make the most efficient use of your time.

9)     Stay productive

When inspiration strikes, jump on it. You don’t have to stick to the traditional three part strategy of completing a PhD- reading, doing, writing. Apart from being a long winded and tiresome method, it might not actually be that productive. If it’s necessary to do some research to back up your writing, then it is fine to read some more.

Or, if it makes more sense to carry out the experiment or data collection over a longer period of time, then do it alongside the reading and writing. There is no right way of working, so just do what is best for you. Just make sure you keep things fresh and moving forward to be successful.

10) Publish

Obviously your PhD is going to be published on completion, but write it up and publish it in various places as you go along. At the natural end of each stage do a write up and publish it online, for example, on your own blog or relevant websites.
Get people excited about what you are doing and keep them in the loop with your progress. Write up each chapter in the form of an article and then rewrite them to encompass your whole PhD.
If you want to learn more about the importance of science blogging and gaining online exposure, check out this post by the Next Scientist:http://www.nextscientist.com/writing-science-blog-saved-phd/
Note: * in above article paragraphs indicates comments contributed by The Grad Student Way (United States specific)

About the Author

Written by Anna Pitts, a Marketing Assistant and Online Researcher at the Graduate Recruitment Bureau. Her work involves PR and outreach and writing informative, interesting advice based articles for graduates and students.

5:26 AM
SOURCE: Cisco
Cisco
Cloud Infrastructure Set to Transform and Facilitate Academic Research in Canada
HAMILTON, ON--(Marketwired - May 8, 2013) - McMaster University and Cisco Canada (NASDAQ: CSCO) today announced they have established a long-term relationship which will see the university increase research activities in Integrated Health Biosystems and Bioinformatics. McMaster and Cisco will also establish a university-wide research cloud computing environment and infrastructure. This partnership will see McMaster build on its renowned research successes and strengthen its links with national and international partners from academia, government and industry. 
As part of the agreement, Cisco is providing a $2.1 million contribution to McMaster. The contribution includes $1.6 million over eight years to establish a Professorship in Integrated Health Biosystems, as well as $500,000 over five years to establish a Research Chair in Bioinformatics.
The Research Chair in Bioinformatics will collaborate on a program in Integrated Health Biosystems, the aim of which will be to bridge the existing gulf between data-intensive areas of biomedical research and healthcare by integrating diverse biological datasets with clinical and environmental data.
The Professorship in Integrated Health Biosystems will help to establish a cloud-based computational infrastructure designed to manage, analyze, integrate and distribute the vast amounts of data resulting from biomedical research, clinical trials, and patient feedback.
Current research initiatives at the university tend to store data in separate databases, accessed primarily by the original research team and seldom shared across different studies. By creating one simple cloud-based infrastructure to both house research data and provide high performance analysis, multiple Faculties at McMaster will have easy access to technology resources, and be able to seamlessly share data and collaborate for a more comprehensive delivery of results. In the future, this "research cloud" could serve multiple institutions and research facilities.
Facts and Highlights:
  • The proposed research cloud will help to lower operating costs for researchers and facilitate the growth of cutting edge areas of research.
  • An institutional research cloud will allow McMaster to quickly grow, change and adapt the computing environment as research needs dictate, through greater flexibility and the quick positioning and migration of computing resources to meet the changing needs of researchers.
  • A cloud-based architecture allows for a bring-your-own-device (BYOD) model of access, granting researchers secure and easy access to sensitive data kept safely on campus, from any resource connected to the internet.
  • McMaster expects the cloud environment will also facilitate research sharing with other universities, institutes and colleges as well as collaborations with industry.
Supporting quotes:
Dr. Patrick Deane, president and vice-chancellor, McMaster University:
"The significance of this partnership with Cisco is enormous. We're home to some of the world's leading researchers who continue to make discoveries through novel approaches and applications. The Chair in Bioinformatics and the Professorship in Biosystems will allow us to increase our research capacity and capture the value of the exponentially increasing volumes of data generated by our researchers. This investment will give us the much needed infrastructure to share our information with our local, national and global partners."
Nitin Kawale, president, Cisco Canada:
"Living in an increasingly connected world brings certain challenges to researchers in terms of managing vast amounts of data and making it easily accessible to the right people for maximum benefit. Cisco and McMaster both realize that this challenge can be turned into a fantastic opportunity to not only improve the way this data is managed, but to also analyze how people's connection to others and to devices continues to evolve. This innovative project has the potential to transform the way academic research is conducted in Canada and throughout the world."
About McMaster University
McMaster University, one of four Canadian universities listed among the Top 100 universities in the world, is renowned for its innovation in both learning and discovery. It has a student population of 23,000, and more than 156,000 alumni in 140 countries.
About Cisco
Cisco (NASDAQ: CSCO) is the worldwide leader in IT that helps companies seize the opportunities of tomorrow by proving that amazing things can happen when you connect the previously unconnected. For ongoing news, please go to http://thenetwork.cisco.com.
Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. A listing of Cisco's trademarks can be found atwww.cisco.com/go/trademarks. Third-party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company.

Contact Information

5:23 AM
Tomorrow, Stanford will host its second TEDxStanford event. The event, which rapidly sold out, is beingwebcasted live beginning at 11 a.m. Pacific Time.
The theme for this year’s event is “Break Through” and the schedule includes an impressive line-up ofspeakers from classrooms and laboratories across campus. Among the group are bioengineer and geneticist Russ Altman, MD, PhD, and electrical engineer Krishna Shenoy, PhD.
Altman leads Simbios, a National Institutes of Health Center for Biomedical Computation at Stanford. His research focuses on how human genetic variation affects drug responses and the analysis of biological molecules to understand the action, interaction and adverse events of drugs. He co-authored a paper published in March showing that the Internet search history of consumers can yield information on the unreported side effects of drugs or drug combinations.
Shenoy, who directs the Neural Prosthetic Systems Lab, works with engineers and neuroscientists to determine how the brain controls movement and to design medical systems to assist those with movement disabilities. He also co-directs the Neural Prosthetics Translational Lab, where these advances are used to help individuals with severe motor disabilities.
As reported in a past Stanford Report story, Shenoy and colleagues studied brain activity in monkeys reaching to touch a target and showed “that the brain activity controlling arm movement does not encode external spatial information – such as direction, distance, and speed – but is instead rhythmic in nature.”
Join the webcast tomorrow to hear more about Altman and Shenoy’s fascinating work and latest research advancements.

5:22 AM
Yaniv Erlich shows how research participants can be identified from 'anonymous' DNA.
Late at night, a video camera captures a man striding up to the locked door of the information-technology department of a major Israeli bank. At this hour, access can be granted only by a fingerprint reader — but instead of using the machine, the man pushes a button on the intercom to ring the receptionist's phone. As it rings, he holds his mobile phone up to the intercom and presses the number 8. The sound of the keypad tone is enough to unlock the door. As he opens it, the man looks back to the camera with a shrug: that was easy.
Yaniv Erlich — the star of this 2006 video — considers this one of his favourite hacks. Technically a “penetration exercise” conducted to expose the bank's vulnerabilities, it was one of several projects that Erlich worked on during a two-year stint with a security firm based near Tel Aviv. Since then, the 33-year-old computational biologist has been bringing his hacker ethos to biology. Now at the Whitehead Institute for Biomedical Research in Cambridge, Massachusetts, he is using genome data in new ways, and in the process exposing vulnerabilities in databases that hold sensitive information on thousands of individuals around the world.
In a study published in January1, Erlich's lab showed that it is possible to discover the identities of people who participate in genetic research studies by cross-referencing their data with publicly available information. Previous studies had shown that people listed in anonymous genetic data stores could be unmasked by matching their data to a sample of their DNA. But Erlich showed that all it requires is an Internet connection.

Security breach

This 2006 video shows Yaniv Erlich penetrating the security features of an Israeli financial institution.
Erlich's work has exposed a pressing ethical quandary. As researchers increasingly combine patient data with other types of information — everything from social-media posts to entries on genealogy websites — protecting anonymity becomes next to impossible. Studying these linked data has its benefits, but it may also reveal genetic and medical information that researchers had promised to keep private — and that, if made public, might hurt people's employability, insurability or even personal relationships.
Such revelations may make the scientific community uncomfortable and undermine the public's trust in medical research. But Erlich and his colleagues see their work as a way to alert the world about flawed systems, keep researchers honest and ultimately strengthen science. In March, for instance, the European Molecular Biology Laboratory (EMBL) in Heidelberg, Germany, claimed that the genome sequence that it had published for the HeLa cell line would not reveal anything about Henrietta Lacks — the source of the cells — or her descendants. Erlich issued a tart response: “Nice lie EMBL!” he tweeted. The sequence was later pulled from public databases, and the EMBL admitted that it would indeed be possible to glean information about the Lacks family from it, even though much of the HeLa genetic data had already been published as part of other studies.
“Most scientists would not go anywhere close to these questions, out of a sense of what it might mean for the field, or for them personally,” says David Page, director of the Whitehead Institute, who has advised Erlich about his research. “But this is not about publicity-seeking — this is about fearlessness, and a kind of interest in how all the parts of the Universe fit together that mark all of Yaniv's work.”

Gaming the system


Erlich was inspired to teach himself programming as a child in Israel after seeing the 1983 film WarGames, in which a teenager accidentally hacks into government computer systems and nearly launches “global thermonuclear war”. Erlich thought that he would study maths and physics at university, but after a friend told him that there was a lot of maths in biology, he decided to major in computational neuroscience. In 2006, following his graduation, Erlich moved to the United States to earn his PhD in genetics at Cold Spring Harbor Laboratory in New York.
Under his adviser, molecular biologist Greg Hannon, Erlich devised what he called “DNA Sudoku”: a sequencing method that could be used on tens of thousands of specimens analysed simultaneously. It allowed scientists to use computational techniques to find a gene carrying a rare mutation from this mixed batch of DNA and assign it to the right specimen2. Erlich is now using the technique to find disease-causing mutations in young Ashkenazi Jews to inform their decisions about potential marriage partners.
In 2011, as Erlich was setting up his first independent lab as a Whitehead Fellow, he met a Colorado-based woman, Wendy Kramer, whose son had managed to track down his father — an anonymous sperm donor — by searching a consumer-focused genetic-genealogy database for people with DNA similar to his own.
Erlich wondered whether a computer program that he had been working on with an undergraduate student, Melissa Gymrek, might enable a similar trick using de-identified genome data from human research studies. The software, called lobSTR, scours sequences and generates a profile of repetitive genetic markers called short tandem repeats (STRs), which are often used in genealogy to identify people. Could Erlich extract STRs from the anonymous data, and then hunt through public genealogy databases for a match and a name? “I had my background in security, and I had lobSTR in hand, and I thought, 'Is this going to affect personal genomes?'”
Erlich and his team tested the idea on a man's full genome that had been published in 2007 (ref. 3). They used lobSTR to determine the STR profile of the man's Y chromosome, and then searched a consumer genealogy database called Ysearch until they had matches with a few likely surnames. Public records on one of these surnames linked it to a man fitting the geographic location and age listed in the paper: the genomics pioneer J. Craig Venter. Venter had, in fact, already revealed himself as the donor — one reason Erlich chose that genome was that he thought he could do no harm in revealing Venter's identity. But there was no reason to believe that this process would not work for others.

Proof of principle

When Erlich submitted his paper to Science, the reviewers wanted proof that a completely anonymous donor could be identified. So his team extended its analysis to men whose genomes had been sequenced as part of the international 1000 Genomes Project. Extensive information about these men, including their ages and detailed family pedigrees, was available on the website of the Coriell Institute for Medical Research in Camden, New Jersey, which distributes cell lines made from their tissues to researchers.
Erlich's team used lobSTR to infer the men's STRs from their 1000 Genomes data, and then searched Y-chromosome databases to find linked last names. After that, it was relatively easy to search public records databases to find men with those last names who were the right age, came from the right place and had similar family trees. The team identified nearly 50 people, including DNA donors and their relatives. When he first saw the results, Erlich said later, he was so shocked at how easily the method worked that he had to go outside and take a walk.
“People were concerned that the NIH would shut down its databases or that the public would stop donating.”
Geneticists elsewhere had already revealed security flaws in anonymized genetic data. In 2008, for instance, David Craig, a computational biologist at the Translational Genomics Research Institute in Phoenix, Arizona, reported that he could use information from an individual's DNA sample to confirm whether that person had contributed to a genome-wide association study (GWAS), even if the study reported only summary statistics on hundreds or thousands of participants4.
This and other studies prompted policy-makers at the US National Institutes of Health (NIH) to pull GWAS data from public databases, and to require investigators to obtain permission to access it. Many researchers resent this move, because it makes it difficult to pool data from different studies.
Erlich's study upped the stakes, because it showed that it was possible to identify people from their genetic data by linking not to other sources of research data, but to information freely available on the Internet. He realized that publishing these results might stoke public anger, so he consulted lots of other researchers and ethicists first. “People were concerned that the NIH would shut down its databases or that the public would stop donating their material,” says Erlich. He contacted NIH officials about his findings, and met some of them in Bethesda, Maryland, last December. The NIH's National Institute of General Medical Sciences, which funds the Coriell repository, decided to remove the ages of participants from public view.

Information withheld

When Erlich published the results of his work in January1, he revealed no research participants' names. Neither did he spell out all the steps he had taken to find their identities: “There is an obvious tension, because as a scientist you want to tell everything about how you did the work. On the other hand, you can't do that, because it will expose people's identities to the world,” says Erlich.
The question remains of how to handle privacy in future. Removing information after loopholes are revealed — what some call the whack-a-mole response5 — does not seem to satisfy anyone.
Some geneticists argue that the public is becoming more accustomed to sharing personal information, and that no harm has ever been done to anyone identified from genetic studies. But many, including Brad Malin a privacy researcher at Vanderbilt University in Nashville, Tennessee, consider that a weak argument. “A lot of people say that because information flows much more freely today than it did 10 years ago, that privacy is dead, and this is certainly not the case,” he says. People still expect some information — especially health and medical data — to be private, says Malin. And so far, none of the people identified from anonymous genetic data sets has been named publicly, so it is perhaps too early to say that they are not at risk.
Eric Green, director of the US National Human Genome Research Institute (NGHRI) in Bethesda, says that the NIH is trying to balance access and privacy. “One value is to make the data as widely available and unencumbered as possible, but then you're trading that off against concerns about how data is being used, and maintaining privacy and confidentiality,” he says. “We're constantly exploring models that put us between those two extremes.”

Careful scrutiny

Currently, anyone with an Internet connection can access data from the 1000 Genomes Project. Researchers must apply for access to genetic data from most other studies, and must usually submit a new access request for information from each one. That makes it onerous to analyse data from different sources together.
Many large data-holders around the world take this approach; the EMBL's European Bioinformatics Institute in Hinxton, UK, for instance, relies on data-access committees to determine what uses of data are appropriate given the consent terms of any particular study. “It's difficult to imagine how else one would do it, since most of these studies are built around consent agreements,” says Paul Flicek, head of DNA resources at the institute.
“Yaniv believes nothing is impossible.”
Some researchers say that genetic data should be deposited with central data-hosting agencies that then grant broad access to trusted users. This would mean that the data would be off-limits to the public, but researchers would not have to ask for permission to access every data set. Laura Rodriguez, director of the NGHRI's division of policy, communications and education, says that NIH committees on data use have concerns about this idea: “We've seen investigators request access to large swathes of data, and it's clear from their proposed-research statement that they haven't read the use limitations of the data they're requesting.”
Erlich argues that genetic data should be broadly available, but that scientists should be more honest about the difficulty of guaranteeing anonymity. Amy McGuire, a lawyer and ethicist at Baylor College of Medicine in Houston, Texas, with whom Erlich consulted on his publication, agrees. But she is not sure that informing people of the risk of re-identification is enough. It may be difficult for someone signing up for a research study to understand all the ways in which their data might be used in the future, let alone to weigh the risks when researchers themselves do not necessarily know them. “There are challenges to putting so much weight on informed consent,” she says.
Scientists should explore further ways to protect research participants, says Erlich, such as encrypting the data before they are deposited, allowing researchers who possess the decryption key to work with them freely without jeopardizing privacy. But Green is concerned that researchers might not be able to work as freely with encrypted data as they can with unencrypted data.
There are no simple answers, but researchers give Erlich credit for forcing these issues onto the public stage. Page warns that this could be a double-edged sword for a young scientist: “This piece of work represents only a slice of Yaniv's broader interests, and the danger could be the risk of being completely consumed by this debate,” he says.
Erlich seems happy to be consumed. In a new project that he calls Genetic Epidemiology 2.0, for example, he is working with Daniel MacArthur, a geneticist at Massachusetts General Hospital and Alkes Price, a biostatistician at Harvard School of Public Health, both in Boston, to mine social networks for information that might yield insight into the genetic basis for complex human traits. The project focuses on genealogy-based social networks on which members post extensive family trees — a potentially rich source of information about inherited traits.
Erlich is aware of the ethical complexities of such a study. To start with, he is focusing on public information about deceased people, to minimize the risk that anyone will be harmed by the work. But if the project succeeds, he may go on to ask members of the networks whether they want to upload other types of information — such as medical records, which could yield insight into a wider range of disease traits.
It is a project that plays to Erlich's strengths, says Hannon. “When Yaniv says, 'What data is out there?' he doesn't think, 'What data is out there in the literature?' He thinks about what data is out there holistically.” If the technique works, it would use information in the public domain to tackle one of the most difficult problems facing genetic researchers: how to assemble the enormous groups of related individuals needed to illuminate the complex genetic underpinnings of human biology. “Yaniv believes nothing is impossible,” says Hannon.
Of course, it could expose all kinds of new vulnerabilities. That may not be such a bad thing, says Erlich, harking back to his penetration testing on banks. “As a client of a US bank, I'm sure you are happy that they undergo these tests. You wouldn't want to say, 'Let's not find something we won't like.'”
Nature
 
497,
 
172–174
 
()
 
doi:10.1038/497172a

5:20 AM

The Human Genome Project, a collaborative effort to sequence the entire human genome, took thirteen years and three billion dollars to complete. This project began in 1990, and, by modern standards, is already considered slow and dated. Today, the human genome can be sequenced in a single day, for only a few thousand dollars.
As sequencing technologies develop, the amount of genomic data that researchers have at their disposal is growing exponentially. To date, 4,327 different species have fully sequenced genomes.
At the intersection of biology and computer science, the field of Bioinformatics has emerged as an important means to process and meaningfully manipulate the wealth of biological data that is available.
Bioinformatics is the field of science involved with using computational methods to convert raw biological data into meaningful biological paradigms. For example, by analyzing sequence and microarray expression data in breast cancer patients, researchers discovered a mutation in the BRCA1 gene associated with a high risk of breast cancer. This bioinformatics study gave researchers a specific target, and studies have since determined exactly how mutated BRCA1 causes breast cancer.
Part I of this article will discuss how bioinformatics data is generated. It will focus on the methods used to collect this data, and the companies that support this collection. Part II will look at how this data is manipulated, discussing the government’s role in archiving and distributing this information. Finally, Part III will explore the real-life applications of bioinformatics, discussing the role of the private sector in applying this data to therapeutic development.
Where does the data come from?
To fully understand the scope of bioinformatics projects, it is important to know how this data originates. Several laboratory methods were recently created to study properties of the cell on a genome-wide scale. In this section, we will focus on three particular methods: Microarrays, Chromatin Immunoprecipitation (ChIP), and DNA Sequencing.

Microarrays
Microarray technology is used to determine the relative expression of a large subset of genes in an organism’s genome. In doing so, a researcher can determine which genes are active in an experimental condition (i.e. disease).
The microarray is a small chip, approximately the size of a standard camera memory card. Thousands of short DNA molecules, called probes, are hybridized to the surface of the chip.
These probes are specifically designed, such that they will adhere to naturally occurring DNA sequences in the cell. A sample of DNA is taken from the cell and added to the chip. When the sample DNA adheres to the probe DNA, a fluorescent signal is emitted. The sum of fluorescent signals comprises the gene expression profile for the cell.
Under different conditions, cells will express different genes. For example, a cell with limited nutrient availability will activate genes involved in breaking down inherent cell components for energy. When nutrients are available, the cell will turn off these genes. When a gene is activated, enzymes first convert the DNA sequence into messenger RNA (mRNA). In microarray experiments, the mRNA from a cell is collected, chemically converted into DNA, and added to microarray chips.
With this technology, a researcher can manipulate a cell, collect the DNA of genes expressed under the new conditions, directly visualize how those manipulations affect the cell’s gene expression profile, and in turn understand what expressions occur under particular conditions.
The concept of a gene chip was conceived in the 1980’s. However, microarray technology, in its modern form, was first introduced in 1997, and its role in the biological sciences continues to grow. Microarrays can now be used to detect a wide array of molecules beyond DNA, including proteins, tissues, carbohydrates, micro-RNAs, and organic chemical compounds (such as drugs).
Several companies, including Affymetrix (AFFX), Illumina (ILMN), and Agilent (A), specialize in the manufacture of DNA microarray chips. These companies have increased a chip’s processing power and simultaneously decreased the amount of a chip’s background noise. Affymetrix’s product, GeneChip, can be used for thousands of simultaneous experiments, for the purpose of direct comparison.
ChIP
Chromatin Immunoprecipitation is a technique used to determine where, specifically, proteins bind onto DNA. DNA-binding proteins are critical to regulation, a fundamental paradigm for pharmaceutical development. Thus, it is becoming increasingly important to precisely understand how these systems function.

In ChIP, cells are initially treated with formaldehyde. Formaldehyde is a crosslinking agent, which stabilizes any chemical interactions in the cell, including protein-DNA interactions. Subsequently, the DNA is extracted from the cell and fragmented mechanically. To isolate the regions of DNA containing the protein of interest, antibody selection is used. Antibodies are designed to interact with a specific protein, and these can be used to filter out any unwanted DNA fragments.
Several companies, such as Abcam (ABC.L), Cell Signaling Technology, and Upstate, specialize in the production of highly specific “ChIP-grade” antibodies. At this stage, the researcher has a collection of the DNA sequences where the protein of interest is bound. Heating the sample separates the DNA and protein.
ChIP can be used to determine local DNA-protein interactions, or it can be paired with DNA microarrays to determine the genome-wide binding profile for a protein of interest. The latter technique, called ChIP-on-chip, illuminates the array of genes to which the protein of interest binds. Since these microarrays have a different function than those for gene expression profiling, a different set of probes must be used. This is because proteins typically bind to regulatory regions, such as promoters or enhancers, which are often found outside of a gene’s coding region. As such, different companies, including NimbleGen and Invitrogen – merged into Life Technologies (LIFE) – manufacture the ChIP-on-chip microarrays.
Sequencing
DNA sequencing is the process of determining the linear order of nucleotide bases within a sample molecule of DNA. Sequencing has innumerable applications in biological sciences, including the identification of mutations, diagnosis of illness, gene therapy, and forensic sciences. By the comparison of DNA sequences, researchers are able to elucidate the molecular mechanisms of potential genetic diseases.

In 1977, Frederick Sanger and colleagues published their Chain-Termination method for sequencing, the first reliable method to sequence long fragments of DNA. Sanger was awarded the Nobel Prize in Chemistry in 1980, and the method is now generally referred to as Sanger sequencing. While technologies have since improved, Sanger sequencing is widely regarded as the breakthrough that allowed DNA sequencing to flourish. Sanger sequencing is the gold standard for first generation sequencing technologies, and was the predominant method used in the Human Genome Project.
DNA is a double-helix comprised of individual units called nucleotides, of which there are four varieties (adenine, thymine, cytosine, and guanine – the A, T, C, and G – that spell out the title of the 1997 science fiction thriller GATTACA). These nucleotides connect to one another vertically, to create single helices, and across, to connect the two helices.
In Sanger sequencing and most second-generation sequencing methods, a single-helix DNA molecule is used as a template, as nucleotides are added across the single-helix to form a double-helix. In Sanger sequencing, a mixture of individual nucleotides and chemically-modified nucleotides are added to the template. The chemical modification prevents further vertical stacking, and, by this approach, researchers can slowly build upon the template and deduce the composition of the sequence.
One decade after the completion of the Human Genome Project, sequencing techniques remain a vital component to laboratory research. While Sanger sequencing laid the foundation, it is, by modern standards, inefficient for larger projects. The method can only sequence up to 800 nucleotides at a time, and the human genome contains roughly four million times that amount. Therefore, it is no surprise that several companies are actively developing new methods to streamline this process.
Pyrosequencing, licensed by 454 Life Sciences, detects a small molecule called pyrophosphate, which is released in the chemical reaction of vertical nucleotide stacking.  Illumina has developed their own method of sequencing, involving fluorescently labeled nucleotides and high-powered cameras to capture which nucleotide is added. Ion Torrent Systems, a subsidiary of Life Technologies, has developed a semiconductor capable of detecting each added nucleotide.
Other companies that are developing DNA sequencing strategies include Oxford Nanopore Technologies (nanopore sequencing), Affymetrix (microarray sequencing), Complete Genomics (DNA nanoball sequencing), Applied Biosystems (SOLiD sequencing), Helicos Biosciences (Heliscope single molecule sequencing), and Pacific Biosciences (single molecule real time sequencing).
With microarrays, ChIP, and DNA sequencing, researchers can accumulate a wealth of biological data. Microarrays depict the genes actively expressed under various conditions. ChIP determines the DNA-binding profile for a protein of interest. Sequencing determines the physical arrangement of nucleotides along the DNA molecule. These techniques are the foundation of bioinformatics.
Bioinformatic researchers (OneMedPlace has coined the term ‘bioinformaticians’) develop complex algorithms to analyze these data, searching for meaningful patterns within this vast stream of information. Ultimately, these findings lead to experiments, discovery, and the development of pharmaceuticals and other therapeutics for debilitating disease. Studies in bioinformatics have already increased our understanding of cancer biology. Only time will demonstrate the full therapeutic potential for bioinformatics.

OneMedPlace Team
About the Author
Through our news, radio interviews, video production, and research,OneMedPlace specializes in delivering information to investors covering nanocap, microcap and private emerging growth companies in the hottest areas of life sciences. OneMedPlace covers what we believe to be an undervalued sector, and has built a network of investors at all levels of financial and strategic development. OneMedPlace produces two investor conferences, OneMedForumSF in January and OneMedForumNY in June, bringing together our diverse network to meet the most promising companies in life sciences. Visit our website to learn more about attending.
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