<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/31302?offset=1300 https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads Thu, 24 Dec 2020 10:03:36 -0600 https://bioinformaticsonline.com/bookmarks/view/42477/hifiasm-a-haplotype-resolved-assembler-for-accurate-hifi-reads <![CDATA[Hifiasm: a haplotype-resolved assembler for accurate Hifi reads]]> Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.

Address of the bookmark: https://github.com/chhylp123/hifiasm

]]> Jit https://bioinformaticsonline.com/opportunity/view/12940/ra-at-iiser-kolkata-computational-biologybioinformatics Wed, 23 Jul 2014 06:24:28 -0500 <![CDATA[RA at IISER Kolkata Computational Biology/Bioinformatics]]> Applications are invited from suitable candidates for research associate (post-doc; Rs. 22000-32000)/research fellow (16000-18000)/project assistant (Rs. 10000-14000) positions in the Department of Biological Sciences, Indian Institute for Science Education and Research Kolkata in the extramural project. Condition to satisfactory performance, the positions is for a period of upto 2 years (or funding of the project).

Brief description: We are looking for suitable candidates in the area o computational biology/bioinformatics/genomics or related field for next-generation sequencing (NGS) data analysis for small-RNAs, RNA-Seq and targeted resequencing of plants and associated organisms. We are an interdisciplinary group where projects equally involve bioinformatics and systems biology (specially microarrays and next-generation sequencing (NGS) data analysis and its use), along with plant molecular biology, genetic engineering, field biology, and analytical plant chemistry for understanding response of plants to biotic stresses.

Essential qualification: MSc/BTech/MTech/PhD (or other suitable qualification) in disciplines preferable to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance Post-Graduate Diploma in Bioinformatics’. Proficiency in programming languages (such as Perl, C++) and/or statistics (proficient in R for example) is compulsory.

Desirable qualification: Experience in the field of genomics e.g. microarray analysis, NGS, genome annotation, database development and management, software development, systems and network biology (or related fields) will be preferred.

Application process: Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by e-mail to Shree Prakash Pandey, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur Campus, WB, India within 14 days of this advertisement.

E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in

Advertisement:

http://www.iiserkol.ac.in/announcements/adverts/671-advt_ra_shree_prakash_july_2014

]]> https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly Tue, 17 Aug 2021 13:17:09 -0500 https://bioinformaticsonline.com/blog/view/43260/bioinformatics-tools-for-telomere-to-telomere-assembly <![CDATA[Bioinformatics tools for telomere to telomere assembly !]]> ● Merfin – k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)
● PanGenie – algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)
● SQANTI3 – an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Rocío Amorín de Hegedüs @rocioadh)
● tama (Transcriptome Annotation by Modular Algorithms) – software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo @GenomeRIK)
● pbaa (PacBio Amplicon Analysis) – separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg @zevkronenberg)
● bellerophon – analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng @Yuanyuan929)
● svpack – tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)
● JumboDB – tool for de Bruijn graph construction (Anton Bankevich @AntonBankevich)
● uLTRA – tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin @krsahlin)
● LeafGo – workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini @ermini_luca)

Reference:

https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/

 

]]> BioStar https://bioinformaticsonline.com/opportunity/view/13276/senior-research-fellow-at-nit-rourkela Wed, 30 Jul 2014 00:53:13 -0500 <![CDATA[Senior Research Fellow at NIT, Rourkela]]> NATIONAL INSTITUTE OF TECHNOLOGY, ROURKELA – 769 008(ORISSA)
SPONSORED RESEARCH, INDUSTRIAL CONSULTANCY & CONTINUING EDUCATION

ADVERTISEMENT NO: NITR/SR/CH-BIF/2014/30

Applications are invited on prescribed format for the following assignment in a purely time bound research project undertaken in the Department of Biotechnology & Medical Engineering of the Institute.

1. Name of the Temporary Post : Senior Research Fellow-01
2. Name of the Research Project: “ Bioinformatics Infrastructure Facility (BIF)”
3. Name of the Sponsoring Agency: DBT, Government of India, 4 Tenure of the Project : 12th Five year Plan
5 Tenure of the Assignment : 01 year [Likely to be extended for 04 more years]
6 Job Description : BIF Maintenance and Active Research in Bioinformatics
7. Consolidated monthly compensation / Fellowship: Rs.18,000/- P.M.

8. Essential Qualifications and experience: B.Tech with valid GATE Score or M.Tech degree in Biotechnology/Bioinformatics/Computer Science/Computational Biology
9. Desirable Qualifications/ Experiences: Experience of Programming in PERL,R, Python, Unix and Visual Studio + Knowledge in NGS data analysis work flows ,WGS and statistical packages such as CRAN-R,MATLAB etc.

10. Accommodation : Bachelor accommodation in the Institute may be provided subject to availability.
11. For technical information on the project, the candidate may contact the Principal Investigator at the following address:

Name : Prof. Mukesh K Gupta
Address : Dept. of Biotechnology & Medical Engineering,
N.I.T.Rourkela-769 008
Telephone No : 0661-2462294
E-mail : guptam@nitrkl.ac.in

Eligible persons may apply in the prescribed format (available in the Institute Website)affixed with coloured photographs to be submitted in duplicate along with photo copies of relevant certificates, grade/ mark sheets, publications etc., to Asst. Registrar, SRICCE,
National Institute of Technology, Rourkela–769 008 before 22.08.2014. The cover should be super- scribed clearly the post applied for & Name of the Project.

Mere possession of minimum qualification does not guarantee invitation to the interview.
Candidates will be short listed based on merit and need of the project.

Advertisement:

http://www.nitrkl.ac.in/IntraWeb/Jobs_Tenders/Jobs/ProjectFellowship/2014/141707192838_1.pdf

]]> https://bioinformaticsonline.com/bookmarks/view/34235/quorum-an-error-corrector-for-illumina-reads Wed, 08 Nov 2017 11:40:41 -0600 https://bioinformaticsonline.com/bookmarks/view/34235/quorum-an-error-corrector-for-illumina-reads <![CDATA[QuorUM: An Error Corrector for Illumina Reads]]> Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.

QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130821

]]> Jit https://bioinformaticsonline.com/opportunity/view/13510/studentship-and-traineeship-in-bioinformatics-at-barkatullah-university-bhopal Thu, 07 Aug 2014 16:57:00 -0500 <![CDATA[Studentship and Traineeship in Bioinformatics at Barkatullah University, Bhopal]]> Department of Biotechnology & Bioinformatics Center
Barkatullah University, Bhopal – 462 026

Studentship and Traineeship in Bioinformatics

Applications are invited on plain paper from suitable candidates for Studentship and Traineeship (One each) at Bioinformatics Sub-Center as detailed below:

1. Studentship: Studentship is for those who have completed M. Sc. Degrees in Life Science.

Number of seats : One

Duration : Six months

Eligibility : Passed M.Sc. degree in Life Sciences.

Fellowship : Rs. 5000/- (Five thousand only) per month

2. Traineeship: Traineeship is for those who have completed M. Sc. Degrees in Life Science/Registered Ph. D. student in Life Sciences.

Number of seats : One

Duration : Six months

Eligibility : Passed M.Sc. degree in Life Sciences/ Registered Ph. D. student in Life Sciences

Fellowship : Rs. 5000/- (Five thousand only) per month

Preferences will be given to person who has experience in Bioinformatics and Computer
sciences. The application along with detailed bio-data should reach the undersigned, on or before 25th August 2014. Both, the studentship and the traineeship are temporary, will be discontinued after the six months from the date of Joining. It may be discontinued in-between without any notice, if the work is not found satisfactory.

Advertisement www.bioinfobubpl.nic.in/Advertisement_st.pdf

]]> https://bioinformaticsonline.com/bookmarks/view/40893/quorum-an-error-corrector-for-illumina-reads Tue, 04 Feb 2020 23:26:55 -0600 https://bioinformaticsonline.com/bookmarks/view/40893/quorum-an-error-corrector-for-illumina-reads <![CDATA[QuorUM: An Error Corrector for Illumina Reads]]> We produce trimmed and error-corrected reads that result in assemblies with longer contigs and fewer errors. We compared QuorUM against several published error correctors and found that it is the best performer in most metrics we use. QuorUM is efficiently implemented making use of current multi-core computing architectures and it is suitable for large data sets (1 billion bases checked and corrected per day per core)

Address of the bookmark: http://www.genome.umd.edu/

]]> BioStar https://bioinformaticsonline.com/blog/view/44758/the-ifs-and-buts-of-ngs-quality-control-and-trimming Thu, 02 Jan 2025 20:11:07 -0600 https://bioinformaticsonline.com/blog/view/44758/the-ifs-and-buts-of-ngs-quality-control-and-trimming <![CDATA[The "Ifs" and "Buts" of NGS Quality Control and Trimming]]> Next-Generation Sequencing (NGS) has revolutionized biological research, providing vast amounts of data for a wide range of applications. However, the reliability of NGS analyses heavily depends on the quality of raw sequencing data. Quality control (QC) and trimming are critical preprocessing steps that can make or break your downstream analyses. In this blog, we explore the "ifs" (why you should perform QC and trimming) and the "buts" (challenges or considerations) of this vital step in NGS workflows.

The "Ifs" of NGS QC and Trimming

  1. Ensures Data Integrity
    If you want to minimize errors in downstream analyses, QC and trimming remove low-quality reads and bases, ensuring high-confidence data. This step is essential for reliable variant calling, assembly, and other applications.

  2. Removes Contaminants
    If adapter sequences or contaminants are present in the raw reads, trimming can eliminate them. This prevents issues like misalignment or incorrect biological interpretations, ensuring cleaner data for analysis.

  3. Improves Mapping and Assembly
    If your goal is better alignment to a reference genome or improved de novo assembly, trimming low-quality bases and adapters is critical. High-quality reads map more efficiently and generate more accurate assemblies.

  4. Reduces Computational Load
    If you want to save computational resources, trimming reduces the dataset size, which speeds up processing and analysis. Clean datasets mean less computational time spent on processing low-quality data.

  5. Prepares for Standardized Analyses
    If your project involves multiple datasets, QC and trimming ensure uniformity across them. This standardization makes comparisons valid and reproducible, particularly in large collaborative studies.

The "Buts" of NGS QC and Trimming

  1. Risk of Over-Trimming
    But excessive trimming can lead to the loss of informative sequences, reducing read depth and potentially discarding biologically relevant data. This is especially critical in studies with limited sequencing depth.

  2. Bias Introduction
    But trimming algorithms might introduce biases, especially if they inadvertently remove sequences with specific biological patterns. This can skew results and compromise biological insights.

  3. Loss of Context in Paired-End Reads
    But trimming one read in a pair more than the other can lead to loss of pairing information. This complicates downstream analyses that rely on paired-end data, such as structural variant detection.

  4. Time and Resource Intensive
    But running QC and trimming for large datasets can be computationally expensive and time-consuming. As sequencing depth increases, preprocessing becomes a bottleneck in the analysis pipeline.

  5. Variable Standards
    But the criteria for trimming (e.g., quality threshold, minimum read length) can vary between tools and datasets. This variability may affect reproducibility and comparability of results across studies.

Balancing the "Ifs" and "Buts"

To maximize the benefits of QC and trimming while mitigating the challenges, consider the following best practices:

  • Use QC Tools Wisely: Start with tools like FastQC to identify quality issues in your raw data. Visualizing quality metrics helps tailor your trimming parameters.

  • Choose Reliable Trimming Tools: Tools like Trimmomatic, Cutadapt, and BBduk offer adaptive and customizable trimming options. Select one that aligns with your dataset and project goals.

  • Set Reasonable Parameters: Avoid over-trimming by setting quality thresholds and minimum read lengths that balance data retention and quality improvement.

  • Test Downstream Effects: Validate the impact of QC and trimming on downstream analyses, such as alignment efficiency, variant calling accuracy, or assembly quality.

  • Document Your Workflow: Maintain detailed records of the parameters and tools used for QC and trimming. This ensures reproducibility and enables better troubleshooting.

Conclusion

NGS quality control and trimming are essential steps to ensure reliable and accurate data for analysis. While the "ifs" highlight the clear benefits of these steps, the "buts" remind us of the potential pitfalls. By adopting best practices and carefully balancing these considerations, you can optimize your preprocessing workflow and unlock the full potential of your sequencing data.

]]> BioStar https://bioinformaticsonline.com/opportunity/view/14183/guest-faculty-at-pondicherry-university Wed, 20 Aug 2014 00:37:57 -0500 <![CDATA[Guest Faculty at Pondicherry University]]> Pondicherry University, India

Walk in interview for guest faculty in Pondicherry University, India. For more information please visit http://www.bicpu.edu.in/bioinfor140814.pdf

]]> https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers Mon, 25 Aug 2014 01:26:19 -0500 https://bioinformaticsonline.com/pages/view/14339/apps-for-busy-bioinformatics-researchers <![CDATA[Apps for Busy Bioinformatics Researchers !!!]]> DNAApp:

DNAApp: for iPhone/iPad

This is an iOS app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", "Copy and Paste sequences", fast and end scrolling, "Chromatogram adjustments", and "Searching for segments" functions.
When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.
This app works with cloud storage access like Dropbox to your sequencing files.
This is now compatible with the new update for iOS 7.1.
Demo video can be found at: https://www.youtube.com/watch?v=mXeo9hXdZgM 

More @ https://itunes.apple.com/us/app/dnaapp/id854944694?mt=8

DNAApp: For android

This is the first android app that allows for the opening and analysis of DNA sequencing files - ab1. It includes handy tools such as "Reverse Complement", "Jump to", fast and end scrolling, "Chromatogram adjustments", amino acid translations, "export to fasta", and "searching for segment" function.

  • When used in combination with other zip apps, and also web-tools like Blast, this app allows you to analyze, and also determine the quality of your sequencing files.
  • This app works with cloud storage access like Dropbox to your sequencing files.
  • This is now compatible with the new update for Android 4.4.2.

More @  https://play.google.com/store/apps/details?id=bii.seqdatreader&hl=en

BioGene:iPhone/iPad

BioGene is an information tool for biological research. Use BioGene to learn about gene function. Enter a gene symbol or gene name, for example "CDK4" or "cyclin dependent kinase 4" and BioGene will retrieve its gene function and references into its function (GeneRIF).

More @  https://itunes.apple.com/us/app/biogene/id333180084?mt=8

Mentha - the interactome browser: Android

About: mentha - the interactome browser, is a project that offers protein-protein physical/enzymatic interaction information from various sources. For more details about mentha, visit mentha's website. This client application is an independent project. This application is designed to allow you to search proteins on the go.

Key features (Also in website):

  • Search proteins by UniProt IDs, gene name or keywords
  • Collect proteins from different queries.
  • Spot common interactors in clusters.
  • Easily distinguish between proteins from Homo sapiens and other organisms (Yellow rounded rectangles)
  • Click on edges(links) to get scientific evidence.
  • Click on proteins to see descriptions.

More @  https://play.google.com/store/apps/details?id=com.sinnefa.mentha&hl=en

GeneIndex: iPhone/iPad

GeneIndex quickly provides information about genes from various sources. It also includes a RSS reader for journal feeds as well as a PubMed viewer.

Key Features:

  • Look up genes by symbol or description.
  • Gene indexes for many mammals, plants, invertebrates, and bacteria.
  • Link to gene info on websites.
  • Download files for offline use. (.pdf, .mp3, .m4v, .doc, .ppt, .xls )
  • transfer files via open in, email, or iTunes file sharing
  • View RSS feeds for journals
  • Query GeneRIF interactions, COSMIC mutations, and CNV data for cell lines.
  • Does not require a network connection for local databases.
  • View and search PubMed in table view.


GeneIndex provides a convenient and portable way to lookup gene symbols while at a seminar, conference, or lab meeting. Genes are linked to common life science websites such as NCBI, COSMIC, KEGG, PubMed, SymAtlas, UCSC genome browser, Pathway Commons, Genatlas, Wikipedia, HUGO, and OMIM. GeneRIF gene interactions can also be queried.

  • Keep current on the scientific literature. GeneIndex includes a RSS reader and web browser for browsing popular journals like Nature, Science, and Cell. You can also add your own RSS feeds. PDFs and podcasts can be saved as files that you can view on the device or email as attachments.
  • Examine the status of genes in common cell lines. A subset of COSMIC containing cell lines can be queried for mutations. Copy Number Variation (CNV) plots from cell lines profiled by GSK and Sanger are also linked to genes.

More @  https://itunes.apple.com/us/app/geneindex/id319769866?mt=8

Genome Voyager: iPad

Gain first hand experience identifying the genomic basis of disease by analyzing cases with whole genome sequencing data that have been published for research and learning purposes.

  • Visualize whole human genome sequencing data including small variations, copy number variations (CNVs), and loss of heterozygosity (LOH) events
  • Quickly find variants of interest by filtering variants based on associated genes, functional impact, allele frequency in data sets, and cross-references with various genomic databases.
  • Collaborate on variant assessments with other researchers and academics to improve knowledge of both pathogenic and benign variants.
    To use Genome Voyager, users must join Genome Voyager’s community of researchers and academics. Visit http://voyager.completegenomics.com to signup.

More @  https://itunes.apple.com/us/app/genome-voyager/id637353801?mt=8

YeastGenome: iPhone/iPad

Use YeastGenome to quickly find fundamental information about Saccharomyces cerevisae genes and chromosomal features. Search gene names, gene descriptions or browse the database to find information about your favorite gene, as well as more detailed information such as Gene Ontology, mutant phenotype, and protein and genetic interaction data.
YeastGenome contains the latest from the Saccharomyces Genome Database (www.yeastgenome.org) in an on bound app database. As more detailed information is presented the app switches to web services access to SGD, and then for even more details provides complete information via hyperlinks to the appropriate SGD database pages.

Key features:

  • Search using gene name or keywords
  • Browse by feature type
  • Save your favorite features
  • Can be used in airplane mode
  • Email information about features to collaborators

What's New in Version 1.8.1

  • This update is required to provide continued functionality. Some of the data provided by this app accesses the SGD service using a method that is changing in May 2013. This version provides changes to allow access to continue. The on board database of yeast gene information has also been updated to March 2013.

More @  https://itunes.apple.com/us/app/yeastgenome/id520868597?mt=8

SNPdbe: iPhone/iPad

SNPdbe — SNP database of effects, with predictions of computationally annotated functional impacts of SNPs. Database entries represent nsSNPs in dbSNP and 1000 Genomes collection, as well as variants from UniProt and PMD. SAASs come from >2600 organisms; ‘human’ being the most prevalent. The impact of each SAAS on protein function is predicted using the SNAP and SIFT algorithms and augmented with experimentally derived function/structure information and disease associations from PMD, OMIM and UniProt.

More @  https://itunes.apple.com/us/app/snpdbe/id588289719?mt=8

SimGene: iPhone/iPad / Android

SimGene: for iPhone/iPad

SimGene is an iPhone/iPad/iPod touch application designed for molecular biologists, bioinformaticians and medical researchers. The application interfaces with Simbiot, Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations and many other databases to retrieve up-to-date annotation information for over 30 species, based on gene symbol search. The application provides gene and transcript cross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene also contains an integrated genome browser with information on genes, transcripts, exons and SNPs.

More @  https://itunes.apple.com/us/app/simgene/id427772349?mt=8

SimGene: for Android

bioinformaticians and medical researchers. The application interfaces with Simbiot,Ensembl, NCBI, Gene Ontology, KEGG Pathways, PubMed, Genomic Variations andmany other databases to retrieve up-to-date annotation information for over 30species, based on gene symbol search. The application provides gene and transcriptcross reference information for NCBI, Ensembl, RefSeq and UniProt. SimGene alsocontains an integrated genome browser with information on genes, transcripts,exons and SNPs.

More @  https://play.google.com/store/apps/details?

TimeTree: iPhone/iPad

TimeTree is a public knowledge-base for information on the evolutionary timescale of life. This application allows easy exploration of the thousands of divergence times among organisms in the scientific literature. A tree-based (hierarchical) system is used to identify all published molecular time estimates bearing on the divergence of two chosen organisms, such as species, compute summary statistics, and present the results. Names of two taxa to be compared are entered in the search window and the results are presented on a set of self-explanatory tabs.

  • TimeTree 3.0 was released September 27, 2011 with new data from 1209 studies including 25342 time nodes. We will be adding more data in the future as it comes in from researchers.
  • TimeTree is jointly directed by Blair Hedges (Pennsylvania State University) and Sudhir Kumar (Arizona State University). This project has been supported, in part, by grants from the National Science Foundation, National Institutes of Health, NASA Astrobiology Institute, and Science Foundation of Arizona.

More @  https://itunes.apple.com/us/app/timetree/id372842500?mt=8

GeneGroove: iPhone/iPad

GeneGroove is the first application to create a music melody from DTC-Genomics data. If you own 23andMe (Mountain View, CA) personal genomic results, GeneGroove will create for you a unique melody intimately based on your 23andMe genome informations. The music in you.

  • After uploading your 23andMe raw data onto your iPhone via iTunes, GeneGroove will analyze your genome informations and generate a unique identifier key. This key, called the GeNumber, will embed the uniqueness of your genome data while keeping your privacy safe, and will be used by GeneGroove to generate your music melody.
  • The GeNumber doesn't contain anymore genomic information but it is based on your genome and it is unique, it is yours. It will be used in upcoming Portable Genomics applications to mix and remix music, manipulate sounds and share your art with your friends and family.

More @  https://itunes.apple.com/us/app/genegroove/id492247404?mt=8

]]> Manisha Mishra