<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/28141?offset=870 https://bioinformaticsonline.com/researchlabs/view/44226/rotifers-lab Wed, 08 Mar 2023 23:23:14 -0600 <![CDATA[Rotifers Lab]]> For scientists in the MBL’s Gribble Lab, the rotifer (Brachionus manjavacas) is used as a model organism to study evolution, stress responses, the biology of aging, and maternal effects. Rotifers are small, easy to grow in the lab, have a short lifespan, and share many of their genes with humans. That makes them ideal specimens in which to address questions relevant to human health as well as understand basic biological and evolutionary processes. Brachionus rotifers produces eggs that can be completely dried and frozen for decades, then hatch within a day when exposed to water and light.

https://www.mbl.edu/research/research-organisms/rotifer
https://gribblebiolab.org/

]]> https://bioinformaticsonline.com/opportunity/view/23924/embl-postdoc-position-in-bacterial-gene-gain-loss Thu, 20 Aug 2015 14:09:21 -0500 <![CDATA[EMBL Postdoc position in Bacterial Gene Gain Loss]]> A post-doctoral fellowship is available in the research groups of Nick Goldman (EBI) and John Welch (Genetics Department, Cambridge University) under the EMBL-EBI / Cambridge Computational Biomedical Postdoctoral Fellowship scheme.

The project is on bacterial gene gain and loss and emerging pathogenicity, and is described in full here: https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015 . The EMBL-EBI / Cambridge Computational Biomedical Postdoctoral (“EBPOD”)

The closing date for applications is 3 September 2015. Nick Goldman EMBL-European Bioinformatics Institute Nick Goldman

More at https://www.ebi.ac.uk/research/postdocs/ebpods/projects/goldman-welch-2015

]]> https://bioinformaticsonline.com/researchlabs/view/5254/mike-ritchie-lab Wed, 02 Oct 2013 15:25:45 -0500 <![CDATA[Mike Ritchie Lab]]> Mike Ritchie Lab primary research focus is the detection of susceptibility genes for common diseases such as cancer, diabetes, hypertension, and cardiovascular disease, among others. The approaches will involve the development and application of new statistical methods with a focus on the detection of gene-gene interactions associated with human disease.

Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/

]]> https://bioinformaticsonline.com/opportunity/view/44727/postdoctoral-scholar-in-bacterial-evolution-at-pathogen-and-microbiome-institute-at-northern-arizona-university Fri, 13 Dec 2024 12:49:16 -0600 <![CDATA[Postdoctoral Scholar in Bacterial Evolution at Pathogen and Microbiome Institute at Northern Arizona University]]> We are pleased to announce a Postdoctoral Scholar position to study
bacterial evolution at the Pathogen and Microbiome Institute at
Northern Arizona University with Professor Paul Keim. The scholar
will have the opportunity also work with Professor Sam Sheppard at
The University of Oxford on joint projects. See our recent paper
on interspecific gene flow in Campylobacter. (DOI:
https://doi.org/10.1128/mbio.00581-24)

The job description: "This research position focuses on the science
of bacterial evolution. It will consist of researching theoretical
principles, but could include translational applications. Phylogenomic
and bioinformatic analysis of bacterial populations in nature or
in laboratory experiments will be a key component of the work. Prior
experience is an asset though training will be possible at PMI.
Likewise, laboratory microbiological, molecular, and biochemical
skills are an asset though not essential. Communication and critical
thinking skills are essential for performing the work and for
communicating to the local and international scientific communities.
Participating in team or independent grant writing to obtain research
funding will be required. Student mentoring is a part of the NAU
mission and is a partial expectation."

https://hr.peoplesoft.nau.edu/psp/ph92prta/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_APP_SCHJOB.GBL?Page=HRS_APP_JBPST&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=608024&PostingSeq=1

Northern Arizona University is located in Flagstaff, Arizona, a
beautiful mountain town with a surprisingly vibrant restaurant
scene. Located a little over an hour from the Grand Canyon and ~45
min from Sedona, Flagstaff is a hiker's paradise. In fact, the city
of Flagstaff operates more than 50 miles of unpaved trails and there
are, on average, 266 sunny days per year with which to enjoy them.
At 7000 ft in elevation, Flagstaff experiences all four seasons,
but thesummers are mild and, in the winter, you can be on the ski
slopes within 30 min! https://www.flagstaffarizona.org/

As mentioned, joint projects with Professor Sheppard at Oxford
University are possible, including travel to his laboratory in the
United Kingdom. https://www.biology.ox.ac.uk/people/samuel-sheppard

Contact Information:
Paul.Keim@nau.edu

Paul S. Keim, Ph.D.
Regents Professor, &
Cowden Endowed Chair of Microbiology
Northern Arizona University
Flagstaff, AZ 86011-4073

Paul S Keim

]]> https://bioinformaticsonline.com/opportunity/view/5403/research-associate-icgeb-new-delhi Wed, 09 Oct 2013 13:49:20 -0500 <![CDATA[Research Associate @ ICGEB, New Delhi.]]> Applications are invited for Research Associate position in the DBT Sponsored Bioinformatics Infrastructure Facility at ICGEB, New Delhi.

Essential requirements: Experience of using bioinformatics tools.

Experience of working in Linux. Basic knowledge of computer network administration.

Desirable: Knowledge of Linux installation/administration and proficiency in either of the following:

Shell/PERL/Java/Python/VB/Oracle/MySQL/C/CUDA.

Qualification: PhD. or First class M.Sc degree in Bioinformatics or Biotechnology/life science with specialization in Bioinformatics.

Fellowships: Rs 22,000/- with HRA for PhD qualified, Rs 16000/- with HRA for NET/BET/BINC/GATE qualified and 12000/- with HRA for non NET qualified applicants.

Interested candidates may send their complete biodata along with a write-up of their experience and suitability for the position to Dr. Dinesh Gupta by email only to dinesh@icgeb.res.in within 15 days of publication of this advertisement. Kindly mark the email with subject “Application for BIF-RA-2013”

Closing date for applications: 18 October 2013

Only short listed candidates will be invited for an interview at ICGEB.

No TA/DA will be paid for attending the interview.

Advertisement: http://www.icgeb.org/tl_files/Vacancies/BIF-RA-Advt.pdf

]]> https://bioinformaticsonline.com/opportunity/view/5574/srfjrfra-university-of-hyderabad Mon, 14 Oct 2013 07:49:11 -0500 <![CDATA[SRF/JRF/RA @ UNIVERSITY OF HYDERABAD]]> SCHOOL OF CHEMISTRY, UNIVERSITY OF HYDERABAD

Applications on plain paper along with details of CV (relevant photocopies of their
qualifications/experience and reprints of published work to be attached) are invited from qualified candidates for Research Fellowship in CSIR- sponsored research project.

JRF/SRF/RA (one vacancy)

CSIR sponsored “In silico design, identification and in vitro validation of lead molecule inhibitors to Bcr-Abl kinase”

JRF: M.Sc in Chemistry/ Bioinformatics/ Biotechnology with I division and NET or GATE qualified

SRF: M.Sc in chemistry/ Bioinformatics/ Biotechnology with at least two years of post- M.Sc research experience as evidenced from published papers in standard refereed journals in relevant area

RA: PhD in chemistry/ Bioinformatics/ Biotechnology with research experience in
relevant area.

As per CSIR guidelines

Notes:
1) You may visit the University of Hyderabad website www.uohyd.ernet.in to learn more about the University of Hyderabad.
2) Applicants should note that the appointment to be made is purely temporary and there is no right for claiming for any regular appointment in the University.
3) No TA/DA will be paid for attending the interview or at the time of joining the post, if selected.
4) The application should be submitted by post/courier/in-person to the address given below on or before November 1st 2013.

Prof. Lalitha Guruprasad
W-103, Gurbakhsh Singh Building
School of Chemistry
University of Hyderabad
Hyderabad- 500 046
5) Short-listed candidates will be called for interview at a short notice.

Advertisement: http://www.uohyd.ac.in/images/recruitment/chemisry_advt_101013.pdf

]]> https://bioinformaticsonline.com/blog/view/44705/pirna-and-bioinformatics-decoding-the-guardians-of-the-genome Sat, 07 Dec 2024 02:15:11 -0600 https://bioinformaticsonline.com/blog/view/44705/pirna-and-bioinformatics-decoding-the-guardians-of-the-genome <![CDATA[piRNA and Bioinformatics: Decoding the Guardians of the Genome]]> In the symphony of small RNAs, PIWI-interacting RNAs (piRNAs) stand out as the protectors of genomic integrity. These small, non-coding RNAs play critical roles in silencing transposable elements, regulating gene expression, and maintaining germline stability. The rise of bioinformatics has revolutionized our understanding of piRNAs, enabling researchers to decipher their biogenesis, functions, and evolutionary significance.

What Are piRNAs?

piRNAs are the largest class of small non-coding RNAs, typically 24–32 nucleotides in length. Unlike microRNAs (miRNAs) and small interfering RNAs (siRNAs), piRNAs do not rely on Dicer enzymes for maturation. Instead, they are processed from long single-stranded precursors and associate with PIWI proteins, a subclass of the Argonaute protein family.

The primary functions of piRNAs include:

  1. Silencing Transposable Elements: By targeting transposons, piRNAs prevent genomic instability, particularly in germline cells.
  2. Regulating Gene Expression: piRNAs modulate gene expression at transcriptional and post-transcriptional levels.
  3. Epigenetic Modulation: They guide epigenetic modifications, such as DNA methylation, to specific genomic loci.

Challenges in piRNA Research

Studying piRNAs is fraught with challenges, including:

  • Short Length: Their small size complicates sequencing and alignment.
  • Lack of Sequence Conservation: Unlike miRNAs, piRNAs exhibit limited sequence conservation across species.
  • Complex Biogenesis: The intricate pathways of piRNA generation require sophisticated computational tools to unravel.

Bioinformatics: Illuminating the World of piRNAs

Bioinformatics has emerged as an indispensable tool for studying piRNAs, facilitating their discovery, annotation, and functional analysis. Here's how bioinformatics is transforming piRNA research:

1. Identification and Annotation

The discovery of piRNAs relies on next-generation sequencing (NGS) data. Bioinformatics tools such as piRNApredictor and Piano identify piRNA clusters and predict potential targets. Databases like piRBase and piRNAdb curate information about known piRNAs, their sequences, and associated proteins.

2. Mapping and Alignment

piRNAs often originate from repetitive regions, making their alignment challenging. Tools like Bowtie and STAR handle the unique mapping requirements of piRNAs, enabling accurate identification of piRNA clusters in genomes.

3. Functional Analysis

Bioinformatics approaches predict piRNA functions by analyzing their interactions with transposons, genes, and epigenetic marks. Algorithms such as TargetFinder and RIblast explore piRNA-mRNA interactions, shedding light on regulatory networks.

4. Evolutionary Studies

piRNAs are evolutionarily diverse, reflecting their roles in species-specific genomic defense. Comparative genomics tools help trace the evolution of piRNA clusters and their associated PIWI proteins across species.

5. Epigenomic Insights

piRNAs are key players in epigenetic regulation. Bioinformatics pipelines integrate piRNA data with chromatin immunoprecipitation sequencing (ChIP-seq) and DNA methylation data to uncover their role in shaping the epigenome.

Case Study: piRNAs in Germline Integrity

One of the hallmark functions of piRNAs is the suppression of transposable elements in the germline. For example, in Drosophila melanogaster, piRNAs target retrotransposons like gypsy and copia. Bioinformatics analyses revealed that these piRNAs guide PIWI proteins to transposon-derived RNA, ensuring genome stability during gametogenesis.

Clinical Relevance of piRNAs

Recent studies suggest that piRNAs may serve as biomarkers for diseases such as cancer, infertility, and neurodegenerative disorders. For instance:

  • Cancer: Dysregulated piRNA expression has been linked to tumorigenesis, making them potential targets for cancer therapies.
  • Infertility: Aberrant piRNA pathways are implicated in male infertility due to their role in spermatogenesis.
  • Neurodegeneration: piRNAs may regulate neuronal gene expression, highlighting their potential in neurological research.

Future Directions

The integration of bioinformatics with emerging technologies offers exciting opportunities for piRNA research:

  • Single-Cell Sequencing: Unveiling cell-specific piRNA expression and function.
  • Machine Learning: Predicting piRNA functions and targets with greater accuracy.
  • CRISPR-Based Tools: Editing piRNA clusters to explore their roles in vivo.

Conclusion

piRNAs are the unsung guardians of the genome, safeguarding genetic material from transposable elements and contributing to gene regulation and epigenetic programming. Bioinformatics has opened the floodgates of discovery, unraveling the complexities of piRNAs and their myriad roles in biology and disease.

As we continue to decode the piRNA landscape, these small RNAs promise to unveil big secrets about genome stability, evolution, and human health, cementing their place as a fascinating frontier in molecular biology.

]]> LEGE https://bioinformaticsonline.com/opportunity/view/5702/research-fellow-in-bioinformatics-queens-university-belfast-institute-for-global-food-security-school-of-biological-sciences Thu, 17 Oct 2013 04:33:02 -0500 <![CDATA[Research Fellow in Bioinformatics @ Queen's University Belfast -Institute for Global Food Security, School of Biological Sciences]]> Ref: 13/102900

Available immediately until 30th November 2015, to work on the development of bioinformatics approaches to aid analysis of data derived from the metabolomic profiling of biological matrices. The successful applicant will lead research activities on an FP7 funded EU-wide collaborative project aimed at establishing biomarker-based strategies for high throughput diagnostic screening. Key tasks will involve multivariate analysis of large datasets, bioinformatic-based selection and validation of identified markers, construction of metabolomic spectral profile databases and development of machine learning/database searching approaches amenable to analytical screening techniques. This position will offer the opportunity to travel and undertake work with project collaborators based in the Republic of Ireland and Europe.

Informal enquiries may be directed to Dr Terry McGrath, email: terry.mcgrath@qub.ac.uk.

Anticipated interview date: Thursday 31st October 2013
Salary scale: £30,424 – £39,649 per annum (including contribution points)
Closing date: Monday 21st October 2013

Telephone (028) 90973044 FAX: (028) 90971040 or e-mail on personnel@qub.ac.uk

The University is committed to equality of opportunity and to selection on merit. It therefore welcomes applications from all sections of society and particularly welcomes applications from people with a disability.

Fixed term contract posts are available for the stated period in the first instance but in particular circumstances may be renewed or made permanent subject to availability of funding.

More @ https://hrwebapp.qub.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=5616943npO&WVID=6273090Lgx&LANG=USA

]]> https://bioinformaticsonline.com/blog/view/44720/a-beginners-guide-to-using-kraken-for-taxonomic-classification Fri, 13 Dec 2024 11:29:03 -0600 https://bioinformaticsonline.com/blog/view/44720/a-beginners-guide-to-using-kraken-for-taxonomic-classification <![CDATA[A Beginner's Guide to Using Kraken for Taxonomic Classification]]> Kraken is a popular bioinformatics tool designed for fast and accurate taxonomic classification of metagenomic sequences. Its efficiency and precision make it a go-to resource for analyzing microbial communities, including bacteria, viruses, archaea, and fungi. Whether you're new to bioinformatics or experienced in the field, Kraken is an indispensable tool for taxonomic analysis.

In this blog, we’ll walk through the basics of Kraken, from installation to running an analysis, and highlight its key features and applications.

What is Kraken?

Kraken is a sequence classification tool that assigns taxonomic labels to DNA sequences using exact k-mer matching. It uses a reference database of genomes, dividing sequences into k-mers and identifying matches in a computationally efficient way.

Key Features of Kraken

  • Speed: Kraken processes data much faster than alignment-based methods.
  • Accuracy: It uses a precise k-mer matching algorithm for high-resolution taxonomic assignments.
  • Scalability: It can handle large metagenomic datasets.
  • Custom Databases: You can build and use custom databases tailored to your research needs.

Installing Kraken

  1. System Requirements

    • A Unix-based operating system (Linux/macOS).
    • Sufficient computational resources for database building (RAM and disk space).

  2. Installation Steps

    • Clone the Kraken repository from GitHub:
       
      git clone https://github.com/DerrickWood/kraken.git cd kraken
    • Compile the Kraken binaries:
       
      make
    • Add Kraken to your PATH for easy access:
       
      export PATH=$PATH:/path/to/kraken

Preparing a Database

Kraken requires a database of reference genomes. You can use a pre-built database or create a custom one.

  1. Downloading a Pre-built Database
    Kraken offers pre-built databases, such as the MiniKraken database, which is lightweight and suitable for smaller datasets. Download it using:

    kraken-build --download-library minikraken

  2. Building a Custom Database
    To include specific genomes, download FASTA files and build the database:

    kraken-build --download-library bacteria --threads 4 --db my_database kraken-build --build --db my_database

    This process may take considerable time and resources, depending on the size of the database.

Running Kraken

Once the database is ready, you can classify sequences.

  1. Basic Usage
    Use the following command to classify sequences:

    kraken --db my_database --threads 4 --fastq-input input_sequences.fastq --output kraken_output.txt

    Key options:

    • --db: Specifies the database.
    • --threads: Number of threads for parallel processing.
    • --fastq-input: Indicates input file format (FASTQ/FASTA).

  2. Interpreting Results
    Kraken generates an output file with columns for sequence IDs, taxonomic classifications, and the confidence score.

Visualizing Kraken Results

Kraken results can be visualized using tools like Krona or converted to human-readable reports using kraken-report.

  1. Generate a Report

    kraken-report --db my_database kraken_output.txt > kraken_report.txt

  2. Krona Visualization
    Install Krona and convert Kraken output for visualization:

    cut -f2,3 kraken_output.txt | ktImportTaxonomy -o krona_output.html

    Open the HTML file in your browser to interactively explore the taxonomic classifications.

Advanced Usage

  1. Confidence Thresholds
    Adjust the confidence threshold for classification using the --confidence option. Higher values reduce false positives but may miss some true positives:

    kraken --db my_database --confidence 0.1 --fastq-input input.fastq

  2. Paired-End Reads
    For paired-end sequencing data, use:

    kraken --db my_database --paired reads_1.fastq reads_2.fastq

  3. Customizing K-mers
    Kraken allows you to set custom k-mer lengths during database building for specific applications.

Applications of Kraken

  • Microbial Ecology: Characterizing microbial communities in soil, water, and the human microbiome.
  • Pathogen Detection: Identifying pathogens in clinical samples.
  • Fungal Research: Analyzing fungal diversity in metagenomic datasets.
  • Environmental Monitoring: Tracking microbial populations in diverse habitats.

Conclusion

Kraken is a versatile and efficient tool for taxonomic classification in metagenomics. Its speed, accuracy, and flexibility make it a favorite among bioinformaticians. By following this guide, you can set up and use Kraken to unlock insights into microbial and fungal communities, paving the way for discoveries in ecology, medicine, and biotechnology.

]]> Neel https://bioinformaticsonline.com/opportunity/view/5947/jrf-national-jalma-institute-of-leprosy-and-other-mycobacterial-diseases Mon, 28 Oct 2013 10:42:48 -0500 <![CDATA[JRF @ NATIONAL JALMA INSTITUTE OF LEPROSY AND OTHER MYCOBACTERIAL DISEASES]]> NATIONAL JALMA INSTITUTE OF LEPROSY AND OTHER MYCOBACTERIAL DISEASES

(INDIAN COUNCIL OF MEDICAL RESEARCH)

P.O BOX 101,
Dr. M. Miyazaki Marg,
Tajganj, Agra - 282001

Applications are invited for a walk-in interview to be held in the Seminar Hall of the on 15th November, 2013, 9:30 am for temporary positions of JRF, Lab Technician and Field attendant in a ICMR funded project entitled "Elucidating the strain differentiation and transmission dynamics of M. leprae through simple sequence repeats ISSR-PCR marker"

1. JRF (one Post)

Essential qualification: Candidates with M.Sc/IVI.Tech or equivalent degree in any life science related subjects with UGC-CSIR/ICMR/DBT-Net qualified

Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.

Age. Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rs. 6,000 + 20% HRA per Month

2. Lab Technician (One Post)

Essential Qualification: 12th with DMLT/B.SCA4.SC in Life sciences

Desirable qualification: Experience in Molecular Biology/Computational Biology will be preferred.

Age: Maximum 30 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rs13,760/ Per Month

3. Field Attendant (One Post)

Essential Qualification: 10th Pass

Desirable Qualification: Experience in field work

Age: Maximum 28 years as on 11.11.2013. Age relaxation as per GOI rules.

Emoluments: Rsl2,040l Per Month

Terms: posts are purely temporary. Appointment will be initially made for a period of one (01) year and may be extended further based on the performance of the candidate up to completion of the project.

Application & Selection procedure: candidates have to appear in the walk-in-interview in person along with an application/CV on plain paper giving details of at educational qualificationq experience and submit photocopies of relevant documents at the time of interview. Selection will be based on the performance of the candidate in the interview' Candidates will not be sent any interview call letter separately. No TA/DA will be paid to the candidate for appearing in the interview. selection is not possible without appearing in the interview. All candidates must report by 9:00am on the date of interview. Advance copy of CV may be sent to m.sarathipartha@gmail.com

Advertisement: http://www.jalma-icmr.org.in/P_S_M_advertisment.pdf

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