sablokgaurav Goto Github PK

👉 I'm based in Germany as Academic Staff Member at Bioinformatics, Institute for Biochemistry and Biology at Universtat Potsdam(UP) and Group 🇩🇪
👉 You can contact me at [email protected] and [email protected]
👉 Highly communicative, motivated, task oriented, feature responsive, time oriented, approachable, solution seeker and initiative taker focussed professional person.
👉 Bioinformatics |  Deep Learning | DevOps | Generative AI | Graphs
👉 Bioinformatics: genomes, transcriptomes, organelle, metagenomes and metatranscriptomes, evolutionary and phylogenome analysis.
👉 Species: plant, bacterial and fungal.
👉 Sequencing platform Illumina, PacBio, Oxford Nanopore.
👉 Deep learning: PyTorch, Tensorflow, CatBoost, XGBoost, Sklearn, Keras and other machine and deep learning
👉 DevOPs: Git,Docker,Kubernetes and Terraform for container orchestration.
👉 Job Scheduler: Skilled in both pbs and slurm. Established computing cluster and blades.
👉 Git management: Github commandline and GitKraken inlcuding stagging, rebasing, stashing, commiting
👉 Generative AI and Graphs.
👉 You can read the curriculum vitae here: curriculum vitae and citations and web of science
👉 You can read the employers references and what they say about me employers.
👉 Open to collaboration on Bioinformatics, Deep Learning, Generative AI, and DevOPs.

👉 I am very pro-active in making communication and upskilling on emerging trends.
👉 Proficient in developing new approaches for better integration and minimal interactions, ease of access approaches.
👉 Profile development by reading about the latest trends in code, personal and professional development.
👉 Prefer office space work but also open to remote work 1-2 days.
👉 Efficient in time and project requirements, approaches and solving limitations.

👉 Currently program:
👉 “Progress thrives on the exchange of knowledge.” (Albert Einstein)
👉 Bioinformatics: Python, R, Ruby, Awk, Shell, Nushell, Scala.
👉 Deep Learning: Python, R, Scala., learning Julia, graphsAPI.
👉 DevOPs: Shell, NuShell, Awk, Ruby, HashiCorp, Python
👉 Web Application: Streamlit, Django, Scala, HTML and Tailwind CSS
👉 Static documentation: Markdown, ReadTheDocs, MKdocs, Jekyll and Ruby
👉 Templating engine: jinja and jinja2, jq and yq
👉 Bioinformatics templating: Nextflow, Snakemake
👉 Previously program: C++

👉 Currently using Linux Linux and plasmakde
👉 Previously using MacBook.
👉 Discord sablokgaurav
👉 Docker applications
👉 journal of open software

👉 tairaccession: python package for interacting with tair: tairaccession
👉 graphanalyzer: python package for analyzing the alignments from the graph alignment tools: graphanalyzer
👉 rnaprocessor: python package for analyzing the sequence for tag based machine learning: rnaprocessor
👉 protein-annotator: python package for analyzing the genome-protein alignments protein-annotator
👉 ontologyanalyzer: python for analyzing the ontologies using the semantic web ontologyanalyzer

👉 devops_system_profiler: a devops system configuration gem: devops_system_profiler
👉 ruby_template_creator: a ruby templating gem creator: ruby template creator
👉 fasta_tokenizer: a fasta tokenizer generator and motif indexer: fasta_tokenizer
👉 panacheextract: a ruby gem for dealing with snps specific information for panache panacheextract
👉 fluxmodels: implementation of all flux models in ruby fluxmodels
👉 protalign: a pre-release protein alignment gem for the genome annotation protein-alignment-gem and proteinmultialign
👉 pacbiohifi-analyzer: analyzing pacbio hifi data from reads to graphs pacbiohifi-analyzer

👉 panachegraph genome graph and nearest neighbour approach in julia-lang to the pangenome graphs. panachegraph

👉 evoseq genome annotation visualization, phylogeny and blocks estimation from protein to genome alignments evoseq, subfunction genomevisual