Past BUG meetings

“The new CQLS HPC infrastructure: Your questions answered!"
- Biocomputing and bioinformatics staff (CQLS)

“The use of high performance computing in the processing and management of large plankton imaging datasets”
- Elena Conser PhD and Marco Corrales Ugalde PhD, Plankton Ecology Laboratory at Hatfield Marine Science Center

“The Genome of the Extraordinary Genus Petalidium, an Aridity Extremophile Endemic to the Hyper-Arid Regions of Namibia. 

“The new CQLS HPC infrastructure: Your questions answered!"

“Gender reveal for oysters? An investigation of early sex determination mechanisms in Pacific oysters, Magallana gigas"

“Introduction to Nanopore Sequencing"

“The Streamwater Microbiome as Hydrologic Observation: Leveraging Community Dynamics to Advance Hydrologic Process Understanding"

“Introduction to Nanopore Sequencing"

“Migrating to the new CQLS HPC infrastructure and SLURM"

“The New Infrastructure and You!"

“Mining NCBI resources to discover new virus species: A case study in molluscan herpesviruses"

“Assembling Eukaryotic Genomes: An overview of current workflows, methods, and future directions."

“A highlight of the AI Efforts and Activities."

“Introducing the hpcman software to automate routine queuing system submission tasks"

“Conda in the CQLS"

“Introduction to Nextflow, a framework for bioinformatics pipeline orchestration"

“Utilizing BRAKER for Gene Annotation in Eukaryotic Genomes"

“Data science careers in Ornamental and Agricultural industries"

“Diverse Data, Diverse Career: From Ecological Restoration to Pharmacological Synthetic Biology"

“Same government, different roles – Insights to a career in public service"

“Career Day Panel: Ask a scientist"

“Bayesian Reinforcement Learning Based Control for Ocean Wave Energy Conversion - i.e., how machine learning/reinforcement learning can improve energy generation from ocean waves"

“The OpenPower HUB - i.e., an open, community driven, sandbox for next-gen HPC"

“The Open Cognitive Environment- i.e., an integrated ecosystem of tools for machine learning"

“TBD"

“Coffee hour with the CGRB; have questions or need help troubleshooting your analyses? Join the CGRB analysts and trainers for an informal / open floor Q&A relating to anything under the umbrella of Bioinformatics and/or Biocomputing"

“DNA soup: Utilizing insect samples and DNA metabarcoding to investigate biodiversity and disease"

“Demography and Clinal Adaptation along the Fundulus heteroclitus Species Range: Inferences from Problematic Sequence Data"

“Molecular Methods for Wildlife Detection and Conservation"

“Pacbio flye assembly and comparison of several Biomphalaria strains and species"

“Navigating Research in Industry and Clinical Biotech i.e. Experiences from a data engineer to give insight into pursuing a career outside academia"

“Cracking the agarikon code: Answering age-old questions about an ancient medicinal mushroom"

“Trading in Pipettes for Python i.e. Switching Gears from the wet lab to data science"

“First A Scholarly, Today Quotidian (FASTQ) Bioinformatician: A sequence of early-career lessons in alignment with bioinformatics"

“Genetic code expansion and augmented metabolism: stop codon repurposing in bacteria, i.e., Faulty annotation in metagenomics means you can't find what you're not looking for"

“Using bilevel optimization to examine antigenic drift in the Influenza A1 virus, i.e., What influences why I need to get a new flu shot every year"

“Using OrthoFinder to identify shared orthologs, i.e., How can we computationally determine what coding sequences are shared between organisms"

“CGRB Disaster Recovery Service, i.e., How to ensure your critical research is being backed up"

“Using Deep Learning and Cloud Computation to Answer Research Questions, i.e. An Undergrad's Journey Through Scientific Computing at the CGRB"

“New Strategies to Develop Hidden Markov Models combining KEGG and Pfams, i.e. Leveraging unannotated sequences to create new Hidden Markov Models"

“A look inside deep learning for bioinformatics, i.e. How do modern neural networks work, and why might they be useful in biology?"

“Getting started with Nanopore sequencing in the lab; i.e. you can do it, and it's not a random sequence generator anymore

“Using genotyping-by-sequencing (GBS) to assess the migratory connections between humpback whale breeding grounds and feeding grounds in the eastern North Pacific Ocean; i.e. 23 & Me for North Pacific humpback whales"

“Wading through Genome Analysis Toolkit’s (GATK) best practices"

“In silico model for mining the cis-regulatory determinants of tissue-specific gene expression"

“An introduction to applied graph databases using Neo4j and Cypher"

“Ensembl's Variant Effect Predictor (VEP) and sequence ontologies to enrich genomic data sets"

“Exploring the chia genome to study essential nutrients biosynthesis"

““R/qtl: applications and methods for analysis of quantitative traits”"

“CERENKOV2: Computational Elucidation of the Regulatory Noncoding Variome, i.e., a machine learning approach to detect the probably most expensive typos in human DNA"

“Biological Knowledge Graphs, i.e., Finding the unknown knowns and dark data in biology"

“What is a replicate? Celebrating the 100th dating anniversary of when statistics met biological experimentation, i.e., Common experimental design issues and consulting services at Department of Statistics"

“Genome analysis of off-target CRISPR mutagenesis in poplar and eucalypts, i.e., Damage control: how often does gene editing happen in the wrong place?"

“Population genomic variation of North Pacific albacore tuna investigated using ddRAD sequencing, i.e., One fish, two fish… where do albacore tuna come from?"

“Machine learning for phenomics and association testing in genome-wide association studies of regeneration in poplar, i.e., how neural networks help us to see the phenes and the genes"

“CGRB’s new DFS for one and all!, i.e., Don’t know what a Distributed File System is? Come find out!"

“A phased, diploid assembly of the hop (Humulus lupulus) genome reveals patterns of selection and haplotype variation, i.e., Resolving functional and evolutionary mysteries of a large, complex plant genome with genomic data science"

“R/qtl, i.e., Applications and methods for analysis of quantitative traits"

“Introductory microbiome analysis using phyloseq, i.e., How to generate exploratory diversity plots and what they mean"

“High-throughput maize ear phenotyping with a custom-built scanner and machine learning seed detection, i.e., Computer counts corn, correctly?"

“IsoSeq pooling and HiSeq multiplexing comparison for Rubus occidentalis samples to explore Aphid resistance, i.e., Utilizing RNA to find differences between  Aphid Resistant and Susceptible plants"