This python script recovers the genbank ids for all the nucleotide entries linked to a taxon id. The number of requests is minimized using the retmax and retstart parameters provided by the Entrez Utilities.

#!/usr/bin/env python
import xml.etree.ElementTree as ET
import sys, urllib, urllib2
eutils_base_url = ""
def get_ids(taxid):
accession_numbers =[]
retstart = 0
iteration_step = 10000
while True:
result = esearch(db = "nucleotide", term = "txid%s[Organism:exp]"%taxid, retstart = retstart, retmax = iteration_step)
result = ET.fromstring(result)
ids = []
if result.find('IdList') is not None:
for id in result.find('IdList').findall('Id'):
result = esummary(db = "nucleotide", ids = ids, retmax = iteration_step)
result = ET.fromstring(result)
for docsum in result.findall('DocSum'):
for item in docsum.findall("Item[@Name='Caption']"):
except Exception, e:
print e
retstart += iteration_step
return accession_numbers
def esearch(db, term, retstart = 0, retmax = 20):
response = urllib.urlopen("%sesearch.fcgi?db=%s&term=%s&retstart=%i&retmax=%i"%(eutils_base_url, db, term, retstart, retmax))
content = str(
return content
def esummary(db, ids, retstart = 0, retmax = 20):
data = {
data = urllib.urlencode(data)
req = urllib2.Request("%sesummary.fcgi"%eutils_base_url, data)
response = urllib2.urlopen(req)
content = str(
return content
if __name__ == '__main__':
taxid = None
if "-id" in sys.argv:
taxid = sys.argv[sys.argv.index("-id")+1]
if not taxid:
print "Usage: -id taxid"
print "Example: -id 4754"
ids = get_ids(taxid)
print ids
print "%i ids found..."%len(ids)

Project title: ESR3: siRomics for universal diagnostics of plant viral disease and virus diversity studies. We are looking for a PhD student with a strong background (master/diploma) in bioinformatics and molecular biology. We shall apply next generation sequencing and bioinformatics to identify and characterize viral pathogens of field crops, grapevines, fruit trees, vegetables and ornamentals in Switzerland. 


Existing methods of viral diagnostics using antibodies and PCR often fail to identify a pathogen. To identify and reconstruct complete viral genomes, we will use a siRNA omics (siRomics) method based on deep sequencing and de novo assembly of short interfering RNAs (siRNAs) which are produced in all virus-infected plants by the evolutionarily-conserved RNA silencing machinery. The main advantage of this method is that it allows fast and reliable characterization of the genomes of newly emerging pathogenic viruses or viral strains and the genetic variation and evolution of viral populations in changing environment. Owing to the global climate changes we expect to detect new viruses that normally occur far away from Switzerland. This study will also be informative for further understanding the mechanisms of RNA silencing-based antiviral defense and for developing novel strategies of virus control such as RNA-based vaccination.

Additional Job Details

Fellowships to graduate students (M.Sc. and Ph.D.) to conduct their research in the laboratory under the supervision of the researchers of the lab. Students must first be accepted to a graduate program in University of Crete. 


Background: The Bioinformatics Laboratory (BIL) is a recent laboratory of the Institute of Computer Science at the Foundation for Research and Technology, Hellas (ICS-FORTH) founded in 2011. BIL is also affiliated with the Computer Science Department of the University of Crete (CSD, UoC): the Head of the lab, Prof. Tsamardinos is also an Assistant Professor at CSD, UoC; additionally, the laboratory offers several fellowships to UoC graduate students. BIL members have pioneered state-of-the-art methods for variable selection, for learning causal models, and most recently for Integrative Causal Analysis, a new approach to learning from multiple and heterogeneous datasets. Overall, FORTH is ranked first among Greek research institutions in number of citations and 12th among European research institutions in EU FP7 funded-project participations. Ph.D. and M.Sc. Student Fellowships: The laboratory offers several fellowships to excellent students from the University of Crete (particularly, the Computer Science Department) supervised by BIL researchers. For M.Sc. students the stipend can be as high as 750 EUR / month, while for Ph.D. students it can reach up to 1000 EUR / month (subject to academic performance and participation in funded research grants). To be eligible for such a fellowship you should first apply and be accepted to a graduate program in the University of Crete (see for procedures). Contact Prof. Tsamardinos for more details. Applications are welcome from students with a computer science background, but also applied mathemetics, engineering, and other related backgrounds are welcome. Preferences: BIL’s contracts are renewed annually. However, we emphasize that BIL is searching to hire and invest on individuals that have a long-term interest in working in the laboratory and build a long-term career in research in general. Location: FORTH is located near Heraklion, the 4th largest city in Greece on the island of Crete. The location is ideal for people who enjoy sunny weather and aquatic activities, or are attracted by the history and archeological sites of the island. FORTH is a multi-national, multi-cultural environment with dozens of foreign students, post-docs, and researchers from around the world. The European Network and Information Security Agency (ENISA) is co-located at the FORTH’s Heraklion campus with employees from all over Europe.

Additional Job Details

For more information contact: Ioannis Tsamardinos Head of Bioinformatics Laboratory Institute of Computer Science, Foundation for Research and Technology, Hellas email: [email protected] Tel: +30 2810 391617 URL: and

Further information

AstraZeneca is a global, innovation-driven, integrated biopharmaceutical company. We are dedicated to discovering, developing, and delivering innovative, meaningful medicines and healthcare solutions that enrich the lives of patients. The vision of AstraZeneca Oncology is to redefine cancer, redefine our solutions to cancer, and restore patients' lives.
The Oncology Bioinformatics Team supports oncology drug projects throughout the discovery pipeline, from new target discovery to early clinical trials. The global group, currently 10 individuals, balances activities between target/disease informatics and drug project informatics. 
There is an exciting opportunity for a talented and motivated bioinformatics scientist to join the group. The successful individual will be a key member of the team, likely supporting translation group to identify genetic/genomic biomarkers for patient selection for late-stage clinical programs. The individual will work with public and proprietary data sets from multiple 'omic and next-generation platforms, integrating these data to identify testable hypotheses.
Encouragement and support will be provided to help the individual develop specialist knowledge and skill sets.
  • Work with translational scientists to identify and support clinical application of genomic biomarkers for patient selection in late-stage clinical programs.
  • Apply computational, statisitical and machine learning capabilities to analyze molecular data from clinical and pre-clincial samples to derive actionable next steps for projects.
  • Identify and validate driver genetic aberrations in next next generation sequencing data (public and proprietary, patients and disease models) .
  • Work closely with cross-disciplinary drug project teams across AZ Oncology UK/US.
    • Understand scientific goals, and identify / suggest informatics solutions.
    • Deliver impactful Bioinformatics support.
    • Work with the bioinformatics group leadership to understand and agree project priorities.
    • Proactively engage in knowledge sharing and peer support to build expertise across the Oncology Bioinformatics group.
    • Conceptualise and develop innovative solutions to enable drug discovery projects to optimally utilise relevant molecular data to support business decisions.
    • Act in accordance with all AstraZeneca policies.

  • Background (degree level) in a biomedical/life science, genetics/genomics, oncology or drug discovery related discipline.
  • Post-graduate qualification, or equivalent experience, in a bioinformatics / genomics / computational-biology related discipline:
  • A Ph.D. in a related scientific discipline, including relevant industry or oncology experience.
  • An MS degree plus at least 3 years experience in a related scientific discipline.
    • First-hand experience in analyzing next generation sequencing (NGS) data, particularly in DNA-sequencing and RNA-seq, to identify variants and gene fusions
    • Experience testing and interpreting biological hypotheses with NGS and 'omic data.
    • Skilled in effective communication of complex genomic data to a non-expert.
    • Innovation recognised through peer reviewed publication in a relevant scientific disciplne
  • Post-doctoral experience in a related discipline.
  • An excellent publication track record in high impact journals.
  • Experience working in a drug discovery, oncology and/or genomics related environment.
  • Experience integrating and interpreting multi-omic data at the network level to uderstand interactions and context specifcity influencing phenotypic class.
  • A good understanding of the contribution of bioinformatics to drug discovery.
  • Well networked within the external bioinformatics community.
  • Knowledge of signaling pathways in Oncology.

Apply now(this will open in a new window)

Further information

Job Title   Bioinformatics Associate Research Scientist (two openings) Department   Computational Biology Job Number   31409   Job Description: 
The Computational Biology (CompBio) Department focuses on the development and application of innovative approaches for analyzing high-throughput; multi-dimensional genomic and epigenetic data generated from basic and clinical research groups studying pediatric cancer, gene therapy and infectious disease. The Department has a well-established track record in developing state-of-art computational methods for analyzing next-generation sequencing (NGS) data with high impact publications in the journals of Nature, Nature Genetics, Nature Methods, JAMA and Cancer Cell. We are looking for highly motivated and talented bioinformatics scientists who are interested in working on a large-scale clinical sequencing project with responsibilities for in-depth analysis of whole-genome, exome and RNASeq data of pediatric cancer patients. CompBio provides a highly collaborative teamwork environment, access to state-of-art computational infrastructure and deep experience in analyzing, managing, visualizing and delivering data and results generated from NGS technology.

The Bioinformatics Associate Research Scientist in the Computational Biology Department is expected to participate in data analysis, data visualization, statistical analysis, experimental design, and database development. Provides bioinformatics analysis for interdepartmental investigators and communicate and discuss with investigators on analytical process and results. Participates in the Computational Biology Department's independent research. Assists in preparing and submitting manuscripts for publication. Contributes ideas to automate or improve existing analysis methods. Assists with establishing and documenting protocols or best practices for common research tasks. Ensures that efficient and prompt help is provided to the SJCRH investigators. (MJP)  
  Job Qualifications: 
PhD in Molecular Biology, Biochemistry, Computer Science, Statistics, Mathematics, Bioinformatics, or related field required. PhD which must include research related to bioinformatics (such as analysis of sequence data, microarrays, SNPs, image data, proteomics data, or biological pathways; development of algorithms, statistical methods, or scientific software); OR If PhD with no bioinformatics research, then two (2) years of pre-or postdoctoral experience in Computational Biology or Bioinformatics research is required.
Experience with programming languages such as Perl, C, or Java required.

Researchers have developed a platform that compiles all the atomic data, previously stored in diverse databases, on protein structures and protein interactions for eight organisms of relevance. They apply a singular homology-based modelling procedure.

The scientists Roberto Mosca, Arnaud Ceol and Patrick Aloy provide the international biomedical community withInteractome3D (, an open-access and free web platform developed entirely by the Institute for Research in Biomedicine (IRB Barcelona).Interactome 3D offers for the first time the possibility to anonymously access and add molecular details of protein interactions and to obtain the information in 3D models. For researchers, atomic level details about the reactions are fundamental to unravel the bases of biology, disease development, and the design of experiments and drugs to combat diseases.
Interactome 3D provides reliable information about more than 12,000 protein interactions for eight model organisms, namely the plant Arabidopsis thaliana, the worm Caenorhabditis elegans, the fly Drosophila melanogaster, the bacteria Escherichia coli andHelicobacter pylori, the brewer’s yeast Saccharomyces cerevisiae, the mouse Mus musculus, and Homo sapiens. These models are considered the most relevant in biomedical research and genetic studies. The journalNature Methods presents the research results and accredits the platform on the basis of it high reliability and precision in modelling interactions, which reaches an average of 75%.
Further details can be found at:
Interactome3D: adding structural details to protein networks by Roberto Mosca, Arnaud Céol and Patrick Aloy. (Nature Methods(2012) doi:10.1038/nmeth.2289)
Network-centered approaches are increasingly used to understand the fundamentals of biology. However, the molecular details contained in the interaction networks, often necessary to understand cellular processes, are very limited, and the experimental difficulties surrounding the determination of protein complex structures make computational modeling techniques paramount. Here we present Interactome3D, a resource for the structural annotation and modeling of protein-protein interactions. Through the integration of interaction data from the main pathway repositories, we provide structural details at atomic resolution for over 12,000 protein-protein interactions in eight model organisms. Unlike static databases, Interactome3D also allows biologists to upload newly discovered interactions and pathways in any species, select the best combination of structural templates and build three-dimensional models in a fully automated manner. Finally, we illustrate the value of Interactome3D through the structural annotation of the complement cascade pathway, rationalizing a potential common mechanism of action suggested for several disease-causing mutations.
Interesting not only for its implications for bioinformatics but for the development of homology modeling (superficially, similar proteins have similar interaction sites) to assist in their work.
The topic map analogy would be to show a subject domain, different identifications of the same subject tend to have the same associations or to fall into other patterns.
Then constructing a subject identity test based upon a template of associations or other values.

RNСОS hаs rесеntlу аddеd а nеw Маrкеt Rеsеаrсh Rероrt titlеd, Вiоinfоrmаtiсs Маrкеt Оutlоок tо 2015 tо its rероrt gаllеrу. During thе раst dесаdе, thе biоinfоrmаtiсs mаrкеt hаs signifiсаntlу еvоlvеd асrоss thе glоbе оn bаск оf rising gеnоmiсs industrу. Тhе inсrеаsing аррliсаtiоn оf gеnоmiсs in biоtесh аnd рhаrmасеutiсаl rеsеаrсh аnd dеvеlорmеnt hаs сrеаtеd а hugе соmmеrсiаl mаrкеt fоr biоinfоrmаtiсs wоrldwidе. Аs реr оur lаtеst rеsеаrсh rероrts еstimаtiоn, thе glоbаl biоinfоrmаtiсs mаrкеt, whiсh rеасhеd thе mаrк оf аrоund US$ 3 Вilliоn in 2010, will ехраnd аt а САGR оf аrоund 25% during 2012-2015 аs thе dесlining соst оf humаn gеnоmе sеquеnсing аnd inсrеаsing рubliс аnd рrivаtе sесtоr invеstmеnt will givе а signifiсаnt bооst tо thе industrу.
Ассоrding tо Вiоinfоrmаtiсs Маrкеt Оutlоок tо 2015, thе соntеnt mаrкеt thаt inсludеs sресiаlizеd аnd gеnеrаlizеd dаtаbаsеs wаs thе biggеst sеgmеnt оf thе glоbаl biоinfоrmаtiсs industrу in 2010, fоllоwеd bу аnаlуsis sоftwаrе & sеrviсеs аnd IТ infrаstruсturе. Аs реr оur аnаlуsis, thе sоftwаrе sеgmеnt is liкеlу tо ехhibit strоng реrfоrmаnсе in futurе, imрrоving its shаrе in thе оvеrаll mаrкеt. Оn thе оthеr hаnd, соntеnt/dаtаbаsе mаrкеt will suffеr thе dоwnturn duе tо thе inсrеаsing рорulаritу оf innоvаtivе аnаlуsis sоftwаrе. Wе hаvе аlsо disсussеd in thе rероrt hоw thе frее dаtаbаsеs wоuld imрасt thе sаlеs оf thе раid оnеs. Оur rероrt аnаlуzеd thе widе аррliсаtiоn оf biоinfоrmаtiсs in gеnоmiсs, рrоtеоmiсs аnd рhаrmасоgеnоmiсs. А furthеr in-dерth studу оf thе mаrкеt rеvеаlеd thаt gеnоmе studiеs hаvе соmрlеtеlу trаnsfоrmеd саnсеr rеsеаrсh in thе раst fеw уеаrs аnd оnсоlоgу hаs bесоmе thе lеаding thеrареutiс аrеа suрроrtеd bу biоinfоrmаtiсs. Wе аlsо оbsеrvеd thаt smаll firms in thе fiеld аrе орting fоr оutsоurсing rоutе tо ехраnd thеir рrеsеnсе. Тhе оthеr кеу trеnds аnd drivеrs рushing thе mаrкеt hаvе аlsо bееn еlаbоrаtеd in thе соmрrеhеnsivе rеsеаrсh studу.
Тhе mаrкеt hаs witnеssеd thе lаunсhеs оf кеу biоinfоrmаtiсs рrоduсts аnd sеrviсеs in vаriоus аrеаs, аnd wе hаvе еvаluаtеd thеsе оn thе bаsis оf thеir соmраniеs аnd соuntriеs in оur rероrt. Тhе rеsеаrсh inсludеs соuntrу-lеvеl аnаlуsis аnd lоокs intо thе rесеnt dеvеlорmеnts thаt mау imрасt thе industrуs futurе реrfоrmаnсе in а signifiсаnt mаnnеr. Ву рrоviding а briеf рrоfilе оf кеу mаrкеt рlауеrs liке Ассеlrуs аnd Аffуmеtriх аnd еvаluаting thеir rесеnt асtivitiеs in thе studу, wе hаvе рrеsеntеd thе industrуs соmреtitivе lаndsсаре. Оvеrаll, thе rероrt аims аt рrоviding аn in-dерth кnоwlеdgе аbоut thе glоbаl biоinfоrmаtiсs mаrкеt tо сliеnts аnd invеstоrs.
Fоr FRЕЕ SАМРLЕ оf this rероrt visit: httр://www.rnсоs.соm/Rероrt/IМ382.htm
Sоmе оf оur Rеlаtеd Rероrts аrе:
- Indiаn Вiоinfоrmаtiсs Маrкеt Fоrесаst tо 2015 (httр://www.rnсоs.соm/Rероrt/IМ412.htm)- Glоbаl Вiоinfоrmаtiсs Маrкеt Оutlоок (httр://www.rnсоs.соm/Rероrt/IМ554.htm)
Сhеск Rеlаtеd RЕРОRТS оn: httр://www.rnсоs.соm/Sсiеnсе%20&%20tесhnоlоgу.htm
RNСОS sресiаlizеs in Industrу intеlligеnсе аnd сrеаtivе sоlutiоns fоr соntеmроrаrу businеss sеgmеnts. Оur рrоfеssiоnаls аnаlуzе thе industrу аnd its vаriоus соmроnеnts, with а соmрrеhеnsivе studу оf thе сhаnging mаrкеt bеhаviоr. Оur ассurасу аnd dаtа рrесisiоn рrоvеs bеnеfiсiаl in tеrms оf рriсing аnd timе mаnаgеmеnt thаt аssist thе intеnding соnsultаnts in mееting thеir оbjесtivеs in а соst-еffесtivе аnd timеlу mаnnеr.

MARI themes

{facebook#} {twitter#} {google#}
Powered by Blogger.