About the author

Senthil Gandi

Gandi is a Ph.D student in Medical Microbiology at the University of Edinburgh. Having graduated with a degree in Biotechnology, merging cool scientific knowledge into industry became his interest. So he worked for two years for a small biotech company and realised doing a Ph.D was the way forward. He has a keen interest for new technologies and always thinking about spreading the great works of Bitesizebio further.

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I couldn’t do without iTunes to store and sort all of my music according genre, artist, album and even fetch the album art from the net. And I always wished there was something like this to sort the gazillion publications that I have in PDF format. Not being a Mac user, I couldn’t use Papers, and of course I like my software free!

Well now my wish has been granted by something called Mendeley, which might just be the best FREE software for research paper management.

As I was testing out this new delight, i could not help noticing that it ticked a lot of my boxes.

For a start this is a cross platform program, meaning, Window, Macs and Linux users can all use this program. The software has been designed in two parts, one is called the Mendeley Desktop and the other is Mendeley Web. Mendeley Desktop is the software that will be installed on your computer to manage your research papers. While Mendeley Web lets you manage your papers on the net, check the current research trends and connect to like-minded researchers.

Below are some of the highlights of this research paper management software

1. Automatic metadata and reference extraction
Just like iTunes, when you drag & drop your PDFs into Mendeley Desktop, it will extract the document’s metadata, keywords and cited references. Also the software is desgined to look up CrossRef DOIs, arXiv IDs and PubMed metadata automatically. This information is used to create a research paper libary in seconds.

2. Full-text search and filters
Once your research paper library has been created, you can do a full-text search on every document and find the context in which the search terms appear.
The search function can be improvised using the filter function. You can filter by authors, journal, keywords or even your own tags.

3. File management, renaming and folder monitoring
One thing that has always annoyed me is when a PDF is downloaded it always has a strange name, such as “1018987as98u1ba.pdf”. These names never make any sense few days after downloading the files. Fear not, with Mendeley Desktop you can manage such files with ease, by renaming them to “Author – Year – Title.pdf”. It even features folder monitoring function, which automatically imports any new file added to a specified folder.

4. Bibliographies in Microsoft Word and OpenOffice
There is a plugin for Microsoft Word users which makes it easy to insert citations into Microsoft Word documents and create bibliographies on the go. The authors have promised an OpenOffice plugin and automatic BibTeX export/LaTeX integration to be incorporated soon as well.

5. Sharing and collaborative annotation
You can also share your impressive research paper library with others. Annotating them collaboratively is also possible. By creating a “Shared Group”, you can invite your colleagues, and drag & drop documents in there.

6. Online management and multi-machine synchronization
Remember earlier I said there is another web part to this software. Well with the Mendeley Web you can sync your documents to your free and private Mendeley Web account. You can now manage and access your documents online as well. And since it is a cross platform program, Mendeley Web makes it possible to merge and synchronize you research paper library even if you use more than one operating system, such as Windows PC at work and a Mac at home.

7. Research trends and statistics
Mendeley collates anonymous statistics about research trends, with these informations, aggregates of most popular authors, papers, journals and tags in your academic discipline are formed.

8. Research profiles and newsfeeds
You will not be alone, you can create a research profile to be discovered by other researchers, it might just be the next �Facebook� for researchers. As you add new publications, awards or conference travels, your colleagues and other researchers will be informed via a newsfeed.

9. Citation capturing in the browser
At the moment Mendeley supports capturing data from ACM Digital Library, Amazon.com, arXiv, Astrophysics Data System, CiteSeer, IEEE Xplore, Google Scholar, Google Books, PubMed, and ScienceDirect. The authors have promised this list will be expanded continuously, and they are also working on integrating with CiteULike.

The official website of Mendeley has more information on downloading instructions, a blog to discuss matters and virtual tour to see more of what is being offered.

The authors always welcome feedback from users, which they take on board to help them improve the software.

I highly recommend that you try Mendeley out and of course tell us what you think about it!

About the author

Carrie Iwema

Carrie is an Information Specialist in Molecular Biology for the Health Sciences Library System at the University of Pittsburgh. She has a PhD in Neuroscience and a Masters in Library Science.

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Today I’m going to tell you about another new genetics resource that’s only been available for a couple of months.

This gem is “YFG (Your Favorite Gene) powered by Ingenuityâ€? and it’s freely available thanks to a partnership between Sigma-Aldrich and Ingenuity Systems.

You read that right, these two for-profit companies are giving researchers something useful for free! Yes, in this economy! Of course, there’s a catch, which I’ll get to…

So what is YFG?

It is a �Web-based biological search portal for exploring dynamic gene-based content.�

YFG combines a search engine from Sigma-Aldrich with Ingenuity’s Knowledge Base, which is a repository of chemical and biological networks .

Researchers can search by gene, pathway, disease, tissue, function, accession number, and more to access biological info and published research findings related to their query.

For example, let’s search using �seasonal affective disorder� or �SAD�, which I’ve used in previous articles (can you tell I’m ready for spring?). The results page lets us know there are 3 genes that match SAD and offers a lot of info about those genes.

Clicking on any of the links next to a particular gene (gene name, Summary, Interactors, Pathways) takes you to another page specific for that gene—we’re going to look at HTR2A. Here you’ll find tabs that offer additional info.

The Gene Details tab provides a summary of info about your gene of interest, including molecular functions, literature references, cellular components, etc. Much of this info is linked to yet more info. It’s a gene info bonanza!

The Interaction Network tab provides an interactive image of molecules or �neighbors� that associate with your gene. Clicking on any of these �neighbors� supplies additional info.

The Canonical Pathway tab provides another interactive image, this time of all of your gene’s pathways and associated molecules. Again, clicking on any of the molecules supplies additional info.

The

Product List tab is one of the catches that allow this tool is free; not surprisingly provides a list of all Sigma-Aldrich products associated with your gene.

However, you are not required to buy anything to use YFG, so don’t let this stop you from trying it out.

The other catch is that although Ingenuity provides a lot of biological network info for YFG, what you can do with that info is limited. If you want to build on the data you’ve found using YFG, you’ll have to actually use another resource called �Ingenuity Pathways Analysis�, which is subscription-based.

Check to see if your institution has a subscription before you sign up for a trial. My institution does have a subscription, and I have to admit that it’s a great tool.

This is just a brief intro to YFG. If you’re interested, I recommend you play around with it, and be sure to watch the tutorial.

And, as always, let us know what you think about it!

About the author

Nick Oswald

Nick is a molecular biologist-turned-publisher. After a PhD in Developmental Biology and an eclectic seven years in biotech he is now Editorial Manager of Neuroendocrinology and the founder and Editor-In-Chief of Bitesize Bio. You are welcome to connect with Nick on LinkedIn

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If you are looking for Omics software, then I suspect the G6G Directory of Omics and Intelligent Software need be your only stop.

From the name it will come as no surprise that this website is a directory of Omics and AI software.

On the Omics side it lists software for Genomics, Cross-omics and Proteomics under the headings:

• Gene Expression Analysis and Profiling
• Gene Expression Databases
• Genomic Data Analysis
• Research Project Design
• Biomarker Discovery and Analysis
• Data and Text Mining Systems
• Knowledgebases and Databases
• Next Generation Sequence Analysis
• Pathway Analysis
• Pathway Knowledgebases and Databases
• Sequence Analysis
• Mass Spec Analysis

Unlike most other software directories, they take the time to provide an abstract about each piece of software they list, together info on system requirements, manufacturer details and links to the manufacturer’s site etc. Also, unlike most other software directories the list will be constantly updated as new software comes in.

But best of all, most of the software they list is free (we love free software lists here at BsB!!).

So this directory put together by the people at G6G is a really useful and comprehensive resource for those looking for free Omics (or AI) software.

Click here to browse the G6G database, or here to sign up to be kept informed about updates to their site.

About the author

Carrie Iwema

Carrie is an Information Specialist in Molecular Biology for the Health Sciences Library System at the University of Pittsburgh. She has a PhD in Neuroscience and a Masters in Library Science.

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Avast, me hearties, I’m back with Part II of our exploration of the HuGE Navigator. To get up to speed, be sure to check out Part I.

In Part II I’m going to go over the HuGEtools, which are used to mine the human genome epidemiology literature. The tools are:

• HuGE Literature Finder
• HuGE Investigator Browser
• HuGE Watch
• Variant Name Mapper
• HuGE Risk Translator
• Gene Prospector

Let’s go over them one by one.

HuGE Literature Finder contains data collected since 2001 (so keep in mind this limitation). It is a search engine for identifying information in the published literature on human genome epidemiology.

The search query can include genes, disease, outcome, environmental factors, author, etc. Results can be filtered by these categories. It is also possible to see all articles in the database for a particular topic, such as genotype prevalence, pharmacogenomics, or clinical trial.

Our Part I search example of �seasonal affective disorder�, aka SAD, brings up 15 articles that can be filtered by 7 genes.

HuGE Investigator Browser helps you search for investigators on human genome epidemiology topics by first/last or all authors. This info is obtained using a behind-the-scenes tool that automatically parses PubMed affiliation data.

Our SAD search results in 17 first/last authors and a total of 73 investigators. Results can be filtered by country or institute.

HuGE Watch helps you track the evolution of published HuGE research. You have a choice to view the trends in the HuGE published literature, HuGE investigators, genes studied, or diseases studied.

For example, if you search �Trend/Pattern� for �Diseases Studied� you’ll initially get a graph and chart of the number of diseases studied per year since 1997. You can refine these results by limiting the temporal trend to a category or study type such as �Gene-gene Interaction� or �HuGE Review�.

Variant Name Mapper lets you map common names of gene variants to theirappropriate rs numbers using information from SNP500Cancer, SNPedia, pharmGKB, ALFRED, AlzGene, PDGene, SZgene, HuGE Navigator, LSDBs, and user submissions.

As an example, one of our SAD genes, HTR2A, mapped to 4 different rs numbers, with 9 different common names, from 7 different sources.

HuGE Risk Translator calculates the predictive value of genetic markers for disease risk. To do so, users must enter the frequency of risk variant, the population disease risk, and the odds ratio between the gene and disease. This information is necessary in order to yield a useful predictive result.

Gene Prospector is �a gateway for evaluating genes in relation to disease and risk factors.� This extremely cool tool allows you to enter a disease or risk factor and then supplies you with a table of genes associated w/your query that are ranked based on strength of evidence from the literature. This evidence is culled from the HuGE Literature Finder and NCBI Entrez Gene. And to show you that it’s all above board, you’re even given the scoring formula.

The Gene Prospector results table provides access to the Genopedia entry for each gene in the list, general info including links to other resources, SNP info, and associated literature from HuGE, PubMed, GWAS, and more. It is a great place to locate a lot of info about your disease/gene of interest very quickly.

To find out more about Gene Prospector, read this article by Wei Yu et al in BMC Bioinformatics.

So now you know the ropes, climb aboard the HuGE Navigator and get ready to explore brave new worlds of genetic associations and human genome epidemiology.

May you find bountiful treasures.

You can discuss your voyages on the HuGE Navigator, or ask any questions in our forum. Use the form below or go to the forum itself to start a new discussion.

About the author

Senthil Gandi

Gandi is a Ph.D student in Medical Microbiology at the University of Edinburgh. Having graduated with a degree in Biotechnology, merging cool scientific knowledge into industry became his interest. So he worked for two years for a small biotech company and realised doing a Ph.D was the way forward. He has a keen interest for new technologies and always thinking about spreading the great works of Bitesizebio further.

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Now you’ve got great sequencing results, thanks to Nick’s article on improving sequencing results. Now what?

Well now you need some software (preferably free) to analyse your data.

BioEdit is a good option. But what I have to offer today is a much lighter and equally handy tool.

It’s called Artemis and was developed by the Sanger Institute. Artemis is a genome viewer, but is extremely handy for viewing and annotating your own sequencing dat (.seq files).

Artemis was covered briefly by Bala in an earlier article on genome viewers.

It is a Java based application, meaning no installation required and for once an application that runs on all three major platforms; Windows, Macintosh and UNIX.

Also, Artemis can be run as a WWW applet, meaning you can view and annotate sequences even when you are on a public computer.

It reads EMBL and GENBANK database entries, or sequences in FASTA or raw format.

I was introduced to this application back in university, but have to say I did not appreciate it until I started working.

So once you get your sequencing data into Artemis, here’s what you can do with it:

• Use the six frame translation function to quickly pull out open reading frames. Unlike BioEdit, Artemis actually shows the corresponding amino acids when stretch of bases is selected and vice versa.

• Plot properties of your sequence, such as G+C content, G/C skew, frame shift G+C content, directly against the sequence and its features.

• Easily zoom from a single base out to the whole sequence (even if it is a genome – it is a genome viewer after all!)

• Easily spot mutations. I do this by having two windows open simultaneously with different zoom levels, making it easier to see where a particular mutation is in respect to the nearby gene and the overall picture.

• Analyse and annotate. The annotation tool allows results from any external analysis programs (EMBL, GENBANK) can be overlaid on the sequence. These can also be modified and moved between files to construct a single annotation table.

One fascinating fact that I discovered about Artemis was during the development stages, the authors used it for the annotation of the complete genomes of Camplylobacter jejuni, Neisseria meningitides and the chromosome of Plasmodium falciparum.

To see more on what Artemis has to offer have a look at the screenshots, you will be amazed at what this simple application can do.

There is even an online demo, which teaches you how to start the program to using all of its functions

Give it a go and tell us what you think about it.

About the author

Paul Hengen

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I love that word. Transmogrified.

It sounds like something Rob Grant and Doug Naylor, the writers of the sci-fi comedy series, Red Dwarf, would make up. As in, “Kryten and I were transmogrified into another time dimension”.

Anyway, enough of 80′s cult TV shows. If you are still with me after the last two articles on using Excel to work your lab results, and you routinely use this business-oriented spreadsheet application for organizing your scientific data, you may be in for a shock. I was!

Yes, it happened to me. Excel polymorphed my gene names into the text equivalent of the mutton vindaloo beast.

So, if you work with lists of gene names, commonly referred to as the “official gene symbol” within MS Excel, be prepared to check your files.

What? How could that happen?

Well, MS Excel was designed to be an office application and not a scientific data organizer, so it thinks it is smarter than you are and automatically converts any data that appears to be a calendar date entry, into a calendar date entry.

Simply double-clicking the filename in windows or opening a data file from the Excel file menu can cause havoc by automatically transmogrifying your gene symbols (names) into a date format.

For example, the gene symbol “Sept1″ will auto-magically be converted to 1-Sep without warning.

How Rude!

That default date format conversion has probably caused more grief to molecular biologists than that dreaded black bulb we used for glass pipettes in first year, or that vacuum suction that pulls only the most precious of samples underneath the lab bench when dropped by accident, and only after weeks of preparation.

To see the transmogrification in action, cut and paste “Sept1″ into a cell within Excel, or create a test file in csv format with some gene symbols in it like “Sept1, DEC2″ etc., try to open it using Excel. The results are not going to be pretty.

Once the deed is done, it is not undo-able, forcing you to start over. And if you inadvertently click the save button and overwrite the original file, you and your data are doomed to an eternity of transmogrification.

The only remedy I know of is to open Excel first, then import the data, changing the default column data type from general to text along the way. Most irritatingly there is no way to turn this auto-format function off (if you know a trick to permanently switch it off, please let us in on it).

Worryingly, many databases containing official gene symbols have been contaminated due to this oversight. Oops! And be careful when using annotation files available from vendors as well… they may have already been transmogrified…!

A huge thanks goes out to Barry Zeeberg [1] and friends for pointing this out.

Has Excel, or anything else, ever transmogrified your data?
And are you a fan of Red Dwarf?

[1] Zeeberg, B.R. et al.
Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics.
BMC Bioinformatics 5:80 (2004)

About the author

Senthil Gandi

Gandi is a Ph.D student in Medical Microbiology at the University of Edinburgh. Having graduated with a degree in Biotechnology, merging cool scientific knowledge into industry became his interest. So he worked for two years for a small biotech company and realised doing a Ph.D was the way forward. He has a keen interest for new technologies and always thinking about spreading the great works of Bitesizebio further.

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BioEdit is a biological sequence alignment editor supreme.

The author of this software calls it an intuitive multiple document interface with convenient features. What an understatement!

At the moment I only use a couple of functions of BioEdit. Mainly I use it to view chromatograms of sequencing results, to do sequence alignments, to reverse complement sequences, and to view amino acid compositions.

The list of functions available is just unbelievable, at the moment my usage only really scratches the surface of it’s capabilities.

The official BioEdit website lists the functions available on BioEdit. Here is just a snapshot of it’s capabilities:

• Four modes of manual alignment: select and slide, dynamic grab and drag, gap insert and delete by mouse click, and on-screen typing which behaves like a text editor.
• In-color alignment and editing with separate nucleic acid and amino acid color tables and full control over background colors.
• Plasmid drawing interface for automated creation of plasmid vector graphic from a DNA sequence. Easily mark positions, add features with arrows and curved boxes, and mark restriction enzyme cut sites. Also show detail of polylinker and draw moveable arrows and shapes with drawing tools.
• Dynamic information-based alignment shading.
• Point-and-click color table editing
• Display and print ABI chromatograms with professional-looking output.
• Group sequences into groups or families.
• Lock alignment of grouped sequences for synchronized hand alignment adjustments.
• Annotate sequences with graphical features with dynamic view in alignment windows including feature annotation information tooltips.
• Lock sequences to prevent accidental edits.
• Specify characters to be considered valid for calculations in amino acid and nucleotide sequences.
• Sort sequences by name, LOCUS, DEFINITION, ACCESSION, PID/NID, REFERENCES, COMMENTS or by residue frequency in a selected column.
• Merge alignments through a reference sequence.
• Append one alignment to the end of another.

If this impresses you, then the full list and the screenshots will blow your mind.

In addition, several sequence manipulation, analysis programs and links to external analysis programs are easily accessible from BioEdit. One of the external applications that I use alot is ClustalW… so that’s one less program I need to run on your computer.

Whether you do a little or a lot of Bioinformatics, I think it is a piece of software that you should definitely try.

The downsides of BioEdit?

Well one is that it only runs on Windows based computers, it is slightly memory demanding, and the author has stopped maintaining this program – although he does offer email-based support.

But nonetheless, as a user of BioEdit I have no complaints. For a freeware program it is simply one of the best pieces of bio-software out there.

If you are looking for more free software, take a look at our top 10 bio-related software for PC and Mac. Or, if you like to keep it in your browser, have a look at what the Molecular Biology toolbar has to offer.

If you have tried BioEdit, tell us your views on the program!

About the author

Carrie Iwema

Carrie is an Information Specialist in Molecular Biology for the Health Sciences Library System at the University of Pittsburgh. She has a PhD in Neuroscience and a Masters in Library Science.

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Ahoy mateys!

At my workplace we’ve recently become EXTREMELY excited about a resource called the HuGE Navigator. It’s so great that it’s going to take me a couple of articles to highlight its features. Hop on board to learn a little about it!

So What is HuGE Navigator?

HuGE Navigator is an integrated set of continually updated applications for accessing data on human genome epidemiology.

This includes gene-disease associations, genetic test evaluations, genetic variance prevalence in certain populations, and gene-gene and gene-environment interactions.

It is a tool for exploring HuGENet, the Human Genome Epidemiology Network, which is

�a global collaboration of individuals & organizations committed to the assessment of the impact of human genome variation on population health & how genetic information can be used to improve health & prevent disease.�

Phew.

HuGENet and HuGE Navigator are supported by the National Office of Public Health Genomics (NOPHG) at the Centers for Disease Control and Prevention (CDC). HuGE has been around since the late 1990s, HuGENet since 2001, and HuGE Navigator since 2007.

Personally, I’m embarrassed that it took me so long to make use of these free resources.

Well, what does HuGE Navigator offer?

For starters, the HuGEpedia, which is an encyclopedia of human genetic variation in health and disease that includes the sub-pedias (ha!) Phenopedia and Genopedia. The former allows you to find information starting with the disease/syndrome name and the latter by gene name.

In general, HuGEpedia is a searchable database that summarizes published articles about human disease and genetic variation, including primary studies, reviews, and meta-analyses. It provides links to Pubmed abstracts , researcher contact info, trends, and more.

For example, type �Seasonal Affective Disorder� (aka SAD) in Phenopedia and you’ll get a list of 7 genes associated w/that disorder. But before we dive into the genes, have a look around the rest of the page.

Clicking on the disease name provides a comprehensive list of synonyms and other info from the Unified Medical Language System (UMLS) Metathesaurus.

Clicking on �Related Diseases� provides a list of connected disease terms stemming from a literature-based disease network (i.e. 2 diseases are connected if they share the same genes).

Using our example, there are 11 disease terms associated with SAD.

Going back to the disease results page, you’ll find that the info is organized in a table format, with an overall summary on the left side of the page that also provides definitions for each of the categories.

A very nice feature here is the link to investigators who have published on your disease of interest.

You can find links to those papers as well as links to all papers by that author that have been indexed in HuGE. The Investigator Browser even divides your query results by all authors versus first/last authors.

The Trend option provides a graph of query publications by year in addition to a Google Map showing the global location of where studies have been conducted. Cool!

Now, onto the disease-related genes themselves.

Let’s start by just going through the table, which can be re-sorted by any of the categories as you see fit.

Clicking on a gene name gives you a long list of links for the following types of info:

• General (Entrez Gene, GeneCard, PharmGKB, etc.)
• Literature (PubMed, HuGE Literature Finder, etc.)
• Gene Variation/Prevalence (dbSNP, SNPper, HGMD, etc.)
• Pathway (KEGG, BioCarta, PID, etc.)
• Microarray (GEO)
• Miscellaneous (NCBI Gene Ontology, GeneTests, etc.)

That is a whole lotta information with a simple click of a mouse.

And there’s more.

Next to each gene name is a link to HuGE-compiled SNP info (such as a list of all synonymous SNPs for that gene) and a link to HuGE-compiled diseases associated with that gene. Using our SAD example, the first gene, SLC6A4, has 209 disease terms associated with it.

Again, lots of info, little effort on our part.

The next column provides a list of and links to PubMed articles on your disease and gene of interest. If you get a lot of results, you can filter them by category, study type, journal, etc.

If there are any Meta-analyses or Genome-Wide Association Study articles on your disease/gene of interest, they are also listed.

Sadly, our SAD example doesn’t currently have any.

Articles on gene environment interaction studies are also provided. The Trend option is the same as described earlier, but specific to the disease-gene combo rather than the overall trend for the disease alone.

The last option of note is that you can re-organize your results according to genes in KEGG pathways. This is a useful option for exploring your disease genes in a functional context.

What About Genopedia?

Well, briefly, Genopedia offers the same type of info, but from the starting perspective of the gene instead of the disease.

Continuing with our SAD example, if we enter the first gene on our list, SLC6A4, into Genopedia, we get that list of 209 associated gene terms (as mentioned earlier).

I’ll leave it to you to continue exploring this database.

This is plenty for now, don’t you think? I’ll be back next time with descriptions of the HuGEtools.

Don’t walk the plank yet—you’ll want to learn about Gene Prospector!

About the author

Suzanne Kennedy

Suzanne is Director of R&D at Mo Bio Laboratories in California, and the author of their blog, The Culture Dish. She has a PhD in Microbiology and Immunology from Virginia Commonwealth University.

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As a scientist in academia or industry, you spend a large portion of your time looking up and reading research papers. What if instead of printing out piles of papers and taking them home to read all weekend, you could click on a video and visualize the experiments and results by the actual researchers doing the work?

Guess what? You can!

The Journal of Visualized Experiments (JoVE) is a new way to publish original methods in the areas of biological and biomedical science in a video format. The focus is on making demonstration of techniques and experimental approaches clear and easy to follow.

Articles published in JoVE are listed in Pubmed and MEDLINE so you can still get your paper cited by other authors. All submissions go through peer review and editorial review and the editorial board consists of 22 distinguished professors from Harvard, Princeton, NIH and other leading institutions in the US, Europe and Japan.

JoVE was created in 2006 by three people; two post-doctoral researchers at the Massachusetts General Hospital, Moshe Pritsker (Ph.D.) and Klaus Korak (M.D.), and a programmer Nikita Bernstein. Their goal was to increase the reproducibility and transparency of experimental studies.

Dr. Pritsker explains

�one of the most difficult �bottleneck� problems of the contemporary biomedical research is repeating biological experiments based on text descriptions in traditional scientific journals. Therefore, more than 50% of the researcher’s time is spent on �reinventing the wheel�, and attempting to reproduce experiments already made and published by someone else. Visualization through online video offers a solution to this problem by providing a clear unambiguous demonstration of experimental techniques and procedures.�

After two years of operations, JoVE has published 23 monthly issues including nearly 300 articles across all the areas of experimental biology including neuroscience, cell biology, developmental biology, stem cell research, immunology, bioengineering and plant biology.

Articles have been produced at leading academic laboratories and research institutions including Harvard, MIT, Berkeley, Stanford, UCSF, Yale and others.

According to JoVE Associate Editor, Mark H. Shalinsky, each video-article is viewed about 5,000 – 10,000 times per year. How many times a year do you think your published paper gets read? Not sure? When you publish on JoVE, you can know exactly how many people were interested in your research.

Submiting your article is easy. Researchers have the option of producing their own video and a written paper (which involves writing the standard sections of a published article- an abstract, introduction, material and methods, results, and discussion) or if production is not possible by the authors, JoVE will send a team to your lab to help shoot the video for you.

JoVE video-professionals are located across 30 cities in the USA, Canada, UK, Germany and Japan including such centers of academic research as Boston, San Diego, San Francisco, New York, Chicago, Seattle, Toronto, Vancouver, London, Berlin, Tokyo and others. The costs of having JoVE produce your video are equal to or less than what you would pay to print in standard top tier journals.

Take a look at some of the interesting work recently published on JoVE.

• The most recent publication is the Purification and Visualization of Influenza A Viral Ribonucleoprotein Complexes
• Do you want to know how to dissect drosophila larvae? Here is a video published by Jonathan Brent, et al., from Columbia University, demonstrating the technique.
• And if you want to know how to collect blood from the American Horseshoe Crab, Limulus Polyphemus, Peter Armstrong from the University of California, Davis is happy to demonstrate.

With visualized experiments you get real-life training on difficult techniques and can share your research with others in a whole new way.

So why not visualize your research? Show to your colleagues and future employees what you actually know without writing – just show!

And think how easy journal club will be when you don’t need to make slides and can just load the video from the JoVE website.

What do you think of JoVE?

About the author

Paul Hengen

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Most available heatmap programs I’ve encountered cost too much, come bundled in a huge application, don’t do what I want, or don’t offer enough flexibility.

In the previous article on heatmaps, I showed how you can use ASAP utilities to sort color-coded cells using this useful Excel Add-in.

What I didn’t tell you is how to create the heatmap in the first
place. So here I’ll show you how you can easily build a color heatmap within an Excel spreadsheet.

Here’s how to do it.

Set up the macro

(1) Copy my the entire text of my handy heatmap macro from this page.
(1) Open Excel
(2) Click on Tools>Macro>Visual Basic Editor (VBE)
(3) In the VBE, double-click on Sheet1 in the upper left corner,
(4) Click here get my handy Excel heatmap macro. Make sure you take all of the text.
(5)Paste the macro text into the code window and close that window by clicking the [X] in the upper right corner.
(6) Close the VBE the same manner

To use the macro

(1) Click on Tools>Macro>Macros (make sure that macros are enabled!)
(2) In the Macro window, you’ll now see the newly created heatmap macro listed
(3) Select it from the list and click the Run box
(4) When you see “Select a range of cells”, mouse over to select the range of cells you want to colorize, then
(5) Click the OK button to color your world.

To change the colors displayed in the heatmap

Go to this webpage (http://www.mvps.org/dmcritchie/excel/colors.htm), find the Excel color codes you want, and edit the macro accordingly.

To test the macro

Make a series of number from 1 to 8 in adjacent cells cells and try to color code them. If you find the number range doesn’t suit your particular purpose, simply edit the macro to change the range of values to be colored.

Good Luck! …and let us know if you have any other macros on hand in your toolbox…