While your PhD or PostDoc application, it is more common that you got rejected by many professors. Don't disappoint reply it calmly.

In grad school, I shared a house with three Bioinformatics PhD students. One, when he applied to a particular professor, received a letter that said, essentially, "If you are applying because you want to enrich yourself, great. If you are applying because you want a job, you should know that you won't get one." I am trying to tell you this is because if you, with a good background in Bioinformatics, are passing up opportunities, you must be a strong candidate in many areas. Enrich yourself.

So, my suggestion is take a deep breath, forgot about all. Don’t take it personally. It's been usual processes while hunting for a good lab and professor. Take is positive, I am not sure why they reject, but don't worry perhaps the lab don't deserve you. Always remember there are billions of reasons not to hire someone for projects, especially in a research sector.

My suggestion, please do not whine about how you were a great research candidate for the post, and you just can't understand why they were so stupid as to have rejected you! This feeling will not win you any points in research, community. Especially, when in todays socially connected era everyone is linked. Remember, a nice E-mail saying, "I really wished to working with you on this project and I hope we cross paths again," is all you need to send to the professor. Send a thank you note to the professor. Thank them for the time they spend to judge you. In the future, If you and the professor (of your dream) are attending a bioinformatics conference, invite him/her to lunch (please remember to pay the bill). In today evolving scientific ere, always remember to build your solid network in order to get a job of interest. Join all possible networking sites like LinkedIn, ResearchGate, Acamedia, FB for the same reason. You as a researcher always build a bridge with student/researcher/colleague/professor who have the research potential to lead in research and hire you. Just because you didn't get this project, doesn't mean there isn't another that will open up in couple of month.

Mostly, jobs that are hard to get are hard to get. Only you can decide if the continued sacrifices are worth the expected payout. If it is, keep on plowing. Build relationships. Attend conferences.

Image ref @ JaSonYa

Reference@http://www.datasciencecentral.com/profiles/blogs/one-page-r-a-survival-guide-to-data-science-with-r

• Templates for the Data Scientist
  1. A Template for Preparing Data: *OnePageR - *R
  2. A Template for Building Models: *OnePageR - *R
• Getting Started as a Data Scientist
  1. Getting Started with R and Rattle: *Lecture - *Laboratory
  2. Introducing and Interacting with R: *Lecture - *Laboratory
  3. BasicR - OnePage(R) - Writing R scripts
• Dealing With Data
  1. Read Data into R: *OnePageR - *R
  2. Explore and Summarise Data: *OnePageR - *R
  3. Transform Data: *OnePageR - *R
  4. Dealing with Dates and Time: (PDF, R) Dates and Time
  5. Visualising Data with GGPlot2: *OnePageR - *R
  6. Visualising Data with Maps *OnePageR - *R
  7. Spatial (R) Spatial Analysis
  8. Handling Big Data *OnePageR - *R
• Descriptive Analytics
  1. Cluster Analysis: *Lecture - *OnePageR - *R
  2. Association Analysis: *Lecture
• Predictive Analytics
  1. Decision Trees: *Lecture - *OnePageR - *R - *Rattle
  2. Ensembles of Decision Trees: *Lecture - *OnePageR - *R
  3. SVM (R)
  4. KernLab (R)
  5. NeuralNetworks (R)
  6. NNet (R)
• Model Delivery
  1. Evaluating Models: *OnePageR - *R
  2. Evaluation (R)
  3. Scoring (R)
  4. PMML (R) Exporting Models for Deployment
• Advanced Topics
  1. Text Mining: *OnePageR - *R
• Advanced R Topics
  1. Plots (PDF, R) Miscellaneous Plots
  2. Functions (PDF, R) Writing Functions in R
  3. Parallel (PDF, R) Parallel Execution
  4. Packaging (R) Pulling it Together into a Package
  5. Doing R with Style: *OnePageR - *R
  6. Literate Data Mining with KnitR: *Lecture - *OnePageR - *

Starting with your current or most recent employment provide details of your position as follows:

• A chronological CV should be arranged in reverse chronological order. It should be apparent immediately where you are now.
• Remember that an application form is limited to the few things that a particular institution wants to know about everybody. A CV lets you give information that is unique to you. Add all your key accomplishments and activities in the initial draft. In subsequent drafts, you can remove information that may not be pertinent.
• Resist the temptation to append explanatory sentences or language, which will distract the reader from the basic information being presented. The language of a CV is abbreviated and succinct. When applying for residency training, you will have the opportunity to express yourself in a personal or biographical statement. In the future, when applying for a job or some other type of position, you will want to include an appropriate cover letter with your CV to explain your particular qualifications and strengths for the position.
• Don’t despair if your CV doesn’t resemble those of other students who are applying to the same residency program. Everybody’s CV is different. Even if everyone used the same format suggested in this section, your CV will not resemble others’ because it doesn’t have the same content. No residency program director is looking for a specific CV style. You will receive points for neatness, and readability.
• Be honest. If you haven’t accomplished anything in a particular category, leave it out. Don’t create accomplishments to fill in the spaces. You can be specific about your level of participation in a project or activity, but don’t be misleading (i.e., you can say you coordinated membership recruitment for your AMSA chapter, but don’t say you were “president” unless you were).

• Job title - time that you have held this position
• The key tasks and responsibilities that comprise this role's requirements - notable achievements whilst in the role
• Where possible quantify your achievements with precise facts and figures, e.g. managed junior staff, handled department budget, prepared management reports
• Expand on the skills you are using in your current job which you believe will be valuable in the position(s) for which you are applying

It is not necessary to state the reason you are leaving your current position. This will be a topic for conversation when you are invited for interview or can be covered in your letter of application.
For all previous employment, unless one appointment was more significant than your current or last position, keep details brief i.e. the name of the company, job title, period of employment and the job.
Be sure there are no gaps in your career history - unless for example you took a year out to travel, in which case make reference to this under Interests/Hobbies.
If you are a student just starting work, give any evidence you can to demonstrate your practical skills e.g. school prefect, event organisation, member of sports team, contributor to college magazine or voluntary work.

You are under no obligation to disclose marital status, age or whether or not you have children unless these are specific criteria for selection for a position that you are interested in.
Consider what examples (interests/ hobbies) you can give to show that you match the selection criteria.

If they want someone to work as part of a large team, remember to say if you belong to a local organisation or if you are part of a sports team.

If they want someone who will work on their own for large periods of time, make reference to an Open University course you are considering undertaking.

Your primary objective is to convince the prospective employer that you have the requisite skills, experience and hunger to do the job.

Your CV should be no more than two A4 pages and as every employer is different remember to customise your CV to every job you go after.

There are abundant books on the contents and presentation of a general CV. A BMJ article published in 1978, offering doctors guidance on how to prepare a CV, has been reprinted in the widely read How to do it series.1 2 A survey among postgraduate deans and training advisers at regional colleges found that the contents and presentation of a model CV for doctors in training has been published.3 It is perhaps surprising to note that these models differ significantly from one another. Although they may be useful as starting points, their differences tend to create confusion and anxiety among students. I would argue that these differences exist because the content and presentation of the "ideal" CV vary considerably among individual applicants, the stage of their careers, and the purposes for which the CV is used. It is impossible to create a generic CV. I have therefore not attempted to draw up another model CV. Rather, the purpose of this article is to outline the general principles and important practical points in preparing a good CV. General principles on contents Before finalising your CV for a particular purpose you must be sure of your objectives, whether it is used as an initial screening or the only selection instrument, and the criteria against which it is judged. What details, and how many of them, to include in your CV depends on these factors. I shall illustrate with examples relevant to medical students. 

(1) Job application Your objective is to get the job. In a job application, the CV is used for two purposes: as an initial screening instrument for shortlisting candidates and as a framework for discussion during the interview. The explicit criteria used for shortlisting are usually given in the job advertisement. For some organisations, separate lists of essential and desirable criteria are given. Alternatively, you can get a good idea of the basic requirements from the job description. Your CV must clearly highlight these criteria, preferably on the first page. These usually include: formal qualifications; registration with the General Medical Council; and the prescribed experience. It is sometimes easy to forget to mention items specifically asked for in the job description (for example, a valid driving licence). The implicit criteria are less easy to pinpoint. For example, how much detail on your BSc dissertation and publications should you include? Should you make a long list of extracurricular activities, interests outside medicine, and positions of responsibility? If you admit to a wide range of extracurricular activities and interests, would you be considered as a candidate with a well balanced mature personality or will it be interpreted to mean that you will have little time or interest to do your job? There are no easy answers. Common sense might tell you that BSc dissertation and publications are more important in application for teaching hospital or research posts, but less important for district hospital posts. Conversely, you might think that interests outside medicine are more important for posts in district hospitals or in general practice. This is, however, not always true. A few consultants at district hospital are highly academic. Information gathered from students and doctors working under the professor or consultant concerned may be vital. Alternatively, it is worth while doing your homework by looking up your prospective consultant in the medical directory. This may occasionally prompt you to include information that you might otherwise have left out. For example, you may find that the consultant qualified in Scotland and has previously worked in Scotland for a considerable time, and you may decide to add in your CV that you studied in a Scottish secondary school. Since the CV is only used as for initial screening, you need not go into your previous experience or extracurricular activities in too much detail. Highlight only the most significant points, and leave the details for the interview. If you are applying for a clinical post, one of your referees should be a consultant for whom you have worked as a student. You should ask for permission to use his/her name before submitting your application. 

(2) Application for research scholarship or PhD studentship The CV and application form are sometimes used as the sole selection instrument, and you must make enquiries before you submit your application. Clearly, academic ability is the main criterion for selection, and you should include as much information relevant to your academic ability and interests as you can. Examples are your A levels, your BSc dissertation, any publications (even in the form of a letter in newspaper), any experience as an editor (for example, for your school magazine). Your extracurricular activities are less important, and you can simply give a short list. At least one of the referees should be an academic - for example, your previous supervisor in your BSc degree.
 
(3) Application to join a clinical course in another medical school Preclinical students who have completed an intercalated degree often have the option of applying to join a clinical course in another medical school, although it may become more difficult to do so with the introduction of the new GMC curriculum. Your CV is usually used for shortlisting candidates for interview. The criteria differ slightly among medical schools, but both academic ability and contribution to university life are important. Hence, not only should you highlight your academic achievements but you must also highlight your participation in the university (for example, in sports or music). 

(4) For the information of your tutor or counsellor For most medical schools, you are allocated a tutor who provides both academic and non-academic support and monitors your progress throughout your study on a confidential basis. Students are sometimes asked to submit their up to date CV to their tutors for information. Assuming that the tutors are helpful there is little to gain from over emphasising your strengths or hiding your weaknesses. Once you become a doctor in training after you qualify you will need to undergo an annual assessment of your progress. It serves to certify that you have reached a satisfactory standard, but it is also used as an aid to identify and help with your weaknesses. You may find it difficult to balance these two purposes in presenting your CV. General principles on presentation Now that all students are computer literate, there should be few problems in preparing a well presented CV. The following list serves as a reminder on how to present your CV effectively: Spelling or grammar mistakes - do not rely purely on the spell check on your computer. Ask friends to proofread your CV for you. Consistency - The use of punctuation to open and close sentences, justification, and fonts should be consistent. Readability - The headings should be clear. The font size should be no less than 12 point. Basic criteria - The basic criteria should be easily located, preferably on the first page. Length - The length of your CV increases as you progress up the professional ladder. For students, it should generally be no more than three pages. Quality of print - The CV should be printed on good quality paper, preferably using a laser printer. Practical points In this article, I argue that different versions of a CV may be required for different purposes. Even applications for different posts in the same specialty may require slightly different versions. Also, CVs need to be updated regularly. This would have been time consuming to achieve in the past, but it is now quite simple, with the aid of a basic word processing package. A master CV containing all relevant information should be prepared and saved as a computer file. This should be continuously kept up to date. When the need for a CV arises, it can be tailormade by editing the master document. It is important to save each of these edited versions separately, with the file names indicating the date when it was created and the purpose. It is also important to prepare a cover letter to go with the CV. Key messages A good CV is essential for successful progression up the medical professional ladder The contents of the CV should be tailormade for the purpose it is used for and the criteria against which it is judged. It is important to gather information about these criteria first The CV must be technically well presented, with the basic criteria easily located Information technology has made it simple to regularly update our CVs and allows preparation of different versions of a CV for different purposes with relative ease.

Reference:

Prepare a curriculum vitae. BMJ 1978;25(2):1478-9.
O'Brien E. Prepare a curriculum vitae. In: Reece D, ed. 
How to do it. Vol 1. London: BMJ Publishing Group, 1995 Chambler AF, Chapman-Sheath PJ, Pearse MF. 
A model curriculum vitae: what are the trainers looking for? Hosp Med 1998;59(4):324-6.

I am Lalit, Working as SRF In Haffkine Institute. I would like to publish research article related to protein modeling and docking which in cludes MD as final step.

I am currently working on protein modeling and docking area. 

Those who are interested . Kindly contact me on this email id:samantlalit@gmail.com

The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo recombination which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.

During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The “chromosomal breakpoints” refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this “break and sealing/ break and reattach” process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities  where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.

Apart from certain chromosome abnormalities, these “crossing over” of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.

I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/  in my next blog.

Software for recombination detection:

RAT http://cbr.jic.ac.uk/dicks/software/RAT/

Breakpointer https://github.com/ruping/Breakpointer

DRP http://web.cbio.uct.ac.za/~darren/rdp.html

RB-finder http://www.ncbi.nlm.nih.gov/pubmed/18707535

LDhat2.0 http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml

Reference:

http://www.nature.com/scitable/topicpage/genetic-recombination-514#

Image: Wikipedia , sciencelearn.org.nz

Recommended Articles:

http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/

http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/

http://learn.genetics.utah.edu/content/disorders/chromosomal/

http://www.ncert.nic.in/html/learning_basket/biology/cc&cd.pdf

1.Stupid for biologist: Biology is so complex that it will make bioinformatician feel stupid. There are no any universal fixed rules; it can surprise you any time. So be nice to biologists who ask questions and resolve your biological puzzles. Sometime you will have no idea what the hell you were doing either.

2.Puzzling why: Do not hesitate to ask question. Especially. at the beginning of project you will have to ask a lot of questions. Instead of puzzling it out at end check out and clear your doubt even for a single error. It may can leads to wrong conclusion.

3.Running marathon: The most of the biological software’s documentation is always incomplete. In other word they are no more than 95 percent complete. Sometime a single problem can halt your entire project for months. Compilation and running the pipelines in tedious because almost all are interdependent and need proper configuration. I face the same kind of problem with Evolver :( …

4.Folders missing: The pipelines generate lots of data, and we keep them in several folders for future use. But sometime we delete them by mistake and move to recovery…

5.Digging deeper: Digging deeper is fruitful, but some time it can be catastrophic. You may get frustrated or direction less. So keep a biologist with you for rescue …. Sometime an expert computer programmer to handle your server. Remember, the server will always go down when you need it the most.

The most common frustrating  common line: Why do we do this again?

sudo /etc/init.d/apache2 stop

sudo /etc/init.d/mysql stop

sudo /etc/init.d/proftpd stop

sudo /opt/lampp/lampp start

PhpMyAdmin “Wrong permissions on configuration file, should not be world writable!”

Once the Xammp is installed, it might be possible to set up the configuration file in writable mode. Try the following steps:

Just chmod 0755 the file

sudo chmod 0755 config.inc.php

1. Update new things continuously
As per my personal experience, it’s not always easy to work as a bioinformatician!  There are couple of reasons to say that; First computational part of biology make our life’s a little harder compared to other professional categories. The fact - for instance - that the technology cycle in the bioinformatics world is very short, the actual knowledge becomes outdated in a few months or years. Therefore, we need to learn continuously - new things get important. Second, to stay on top of things we really need the strong will to be good at our job. That's probably the most important characteristic to bioinformatician. They are usually an excellent knowledge worker with great technical abilities, and have the will to be that over decades!

2. Avoid the sentence "I did not know what to do!"
In our computational biology lab, we generally face lots of technical problems. But as you know, it's impossible to know everything to do the computational biology jobs ( Yup.. because you need diverse and multidisciplinary knowledge to understand biological problems and resolve their respective solutions), therefore it's absolutely necessary that a bioinformatician finds its way through a new topic. How I typically do that is I use google and I talk to other experts in our laboratory or online biostar community to find out what they think. "I did not know what to do!" should not be an argument for us.

3. To make oneself useful
Several time it does happen, you finished our task earlier than expected; in such cases if you have some time left then: Take a coffee and play chess; reversi, etc. In my case I take a rest. Afterwards I think about what I could do that helps the team to achieve its targets, 'cause some of my team mates probably didn't finish! (at least if I didn't met them at coffee bar !!)

4. Care for all
During my rigorous research duration; I attended several workshop organized by my University departments. I had a discussion with other research fellow, professors; I generally ask … what it really takes to make a team successful or to be a successful research leader. They always said: "Well, you need some caring people!" I think there is a lot truth in that statement. If we do not care about quality, timelines, good team culture, respectful communication (!!), clean code, if all this doesn’t matter to us, then I believe the probability is higher that we fail in research and analysis.

5. Be good with people
Because bioinformatician and computational biologist jobs typically involves to work in a (most wanted J cross-departmental!) team, therefore it's important that we're (more or less) good in dealing with other individuals. Everyone have their own strengths and weaknesses, just like us. It's important to treat all the research team mates with respect, regardless of their technical competence or contributions. Of course, sometimes people deserve a clear statement (!!!), but try to do these things one-on-one. Make sure nobody loses his face. Attend the meetings at the coffee bar; be good at table top soccer and go out once in a while to have a beer with your team. You know what I'm talking about.

At the end of a week I look back and I ask myself what I have produced. This could be paperwork, community days or (best!!) programming code. Always remember there is always a solution to a problem. Most of the times there are at least three solutions. So, don’t just blame, suggest a solution.

That's it. I am looking forward to your thoughts and comments!

The GO provides core biological knowledge representation for modern biologists, whether computationally or experimentally based. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Although extensively used in data analysis workflows, and widely incorporated into numerous data analysis platforms and applications, the general user of GO resources often misses fundamental distinctions about GO structures, GO annotations, and what can and can not be extrapolated from GO resources. Here are ten quick tips for using the Gene Ontology.

Read "Ten Quick Tips for Using the Gene Ontology" at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003343

Following are the most commonly used old and new GO term enrichment determination tools. These tools are recommended to people working in a wet-lab.

CLASSIFI (Department of Pathology, UT Southwestern Medical Center)

CLASSIFI (Cluster Assignment for Biological Inference) is a data-mining tool that can be used to identify significant co-clustering of genes with similar functional properties (e.g. cellular response to DNA damage). Briefly, CLASSIFI uses the Gene OntologyTM (GO) gene annotation scheme to define the functional properties of all genes/probes in a microarray data set, and then applies a cumulative hypergeometric distribution analysis to determine if any statistically significant gene ontology co-clustering has occurred.

http://pathcuric1.swmed.edu/pathdb/classifi.html

EasyGO (China Agricultural University)

EasyGO is designed to automate enrichment job for experimental biologists to identify enriched Gene Ontology (GO) terms in a list of microarray probe sets or gene identifiers (with expression information for PAGE analysis). Also EasyGO is also a GO annotation database, especially focus on agronomical species, supporting 30 species. It is user friendly, with advanced result browsing format and in-time update.

http://bioinformatics.cau.edu.cn/neweasygo/

http://bioinformatics.cau.edu.cn/easygo/

g:GOSt (Institute of Computer Science, University of Tartu)

g:GOSt retrieves most significant Gene Ontology (GO) terms, KEGG and REACTOME pathways, and TRANSFAC motifs to a user-specified group of genes, proteins or microarray probes. g:GOSt also allows analysis of ranked or ordered lists of genes, visual browsing of GO graph structure, interactive visualisation of retrieved results, and many other features. Multiple testing corrections are applied to extract only statistically important results.

http://biit.cs.ut.ee/gprofiler/

DAVID : Gene Functional Classification (Laboratory of Immunopathogenesis and Bioinformatics, NIAID)

The Functional Classification Tool provides a rapid means to organize large lists of genes into functionally related groups to help unravel the biological content captured by high throughput technologies.

http://david.abcc.ncifcrf.gov/gene2gene.jsp

http://david.abcc.ncifcrf.gov/

API https://github.com/chrisamiller/davidapi

GOEAST (Institute of Genetics and Developmental Biology, Chinese Academy of Sciences)

GOEAST is web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods.

http://omicslab.genetics.ac.cn/GOEAST/

GOstat (Walter and Eliza Hall Institute of Medical Research)

Find statistically overrepresented GO terms within a group of genes

http://gostat.wehi.edu.au/

GOrilla (Technion - Laboratory of Computational Biology , Israel Institute of Technology)

GOrilla is a tool for identifying and visualizing enriched GO terms in ranked lists of genes.
It uses two approaches, first by searching for enriched GO terms that appear densely at the top of a ranked list of genes  or by searching for enriched GO terms in a target list of genes compared to a background list of genes.

GOrilla makes nice pictures !!!!

http://cbl-gorilla.cs.technion.ac.il/

Gene Ontology for Functional Analysis (GOFFA)

GOFFA is a tool developed for ArrayTrack™ that takes a list of genes and identifies terms in Gene Ontology (GO) disclaimer icon associated with those genes.

It provides several tools to view/access the GO term hierarchy, full listing of GO terms annotated with the genes associated with a given term with statically useful report.

http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm233315.htm

GOAT (The University of Manchester)

The aim of the GOAT project is to create an application that will guide users, especially biomedical researchers, in the annotation of gene products with terms from the Gene Ontology.

http://goat.man.ac.uk/

Script https://github.com/tanghaibao/goatools/

REVIGO ( Rudjer Boskovic Institute, Croatia)

REViGO is a web server that can take long lists of Gene Ontology terms and summarize them by removing redundant GO terms. The remaining terms can be visualized in semantic similarity-based scatterplots, interactive graphs, or tag clouds.

http://revigo.irb.hr/

QuickGo (EMBL-EBI Institute)

It uses extensive computational filters to allow the generation of specific subsets of GO annotations, mapped to sequence identifiers of your choice. Then GO slims are used which is collective list of GO full set of terms available from the Gene Ontology project.

http://www.ebi.ac.uk/QuickGO/

GOLEM

An interactive graph-based gene-ontology navigation and analysis tool. GOLEM is a userful tool which allows the viewer to navigate and explore a local portion of the Gene Ontology (GO) hierarchy.

http://reducio.princeton.edu/GOLEM/

BGI Web Gene Ontology (WEGO) Annotation Plot (Beijing Genomics Institute)

WEGO () is a useful tool for plotting GO annotation results. It has been widely used in many important biological research projects, such as the rice genome project [Yu, J. et al. Science 296, 79-92 (2002); Yu, J. et al. PLoS Biol 3, e38 (2005)] and the silkworm genome project [Xia, Q. et al. Science 306, 1937-40 (2004)]. It has become one of the daily tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. WEGO along with two other tools, namely External to GO Query and GO Archive Query, are freely available for all users. Any suggestions are welcome at wego@genomics.org.cn. Here is a sample output generated by WEGO

http://wego.genomics.org.cn/cgi-bin/wego/index.pl

GeneGO MetaCore (MIT)

GeneGo is a leading provider of data mining & analysis solutions in systems biology. MetaCore, GeneGo's flapship product, is an integrated software suite for functional analysis of experimental data. MetaCore is based on a curated database of human protein-protein, protein-DNA interactions, transcription factors, signaling and metabolic pathways, disease and toxicity, and the effects of bioactive molecules.

https://portal.genego.com/

GOEx (Stony Brook University)

GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics.

http://pcarvalho.com/patternlab

GOssTo

GOssTo and GOssToWeb are tools to calculate the semantic similarity between genes or terms in the Gene Ontology.

http://www.paccanarolab.org/gosstoweb/

GO Workbench

The Gene Ontology Analysis Viewer allows direct browsing of the Gene Ontology, and also the visualization of GO Term analysis results.

http://wiki.c2b2.columbia.edu/workbench/index.php/Gene_Ontology_Viewer

Some other useful list of GO software and tools is available at http://www.geneontology.org/GO.tools.shtml#browser

Yet another useful webpage with list of GO tools at http://neurolex.org/wiki/Category:Resource:Gene_Ontology_Tools