nucleic acids & proteins 

 

vectors

creation of bacterial, viral and retroviral constructs, enzymatic cleavage and ligation, transfection and transformation, construct purification and concentration

screening & quantification

multiplex & high-throughput screening/assays, Luminex sequencing, dye-terminator sequencing, western blotting & immunoprecipitation, PCR, RT-PCR, qPCR, RT-qPCR, SDS-PAGE & agarose gel electrophoresis, ELISA & ELISPOT, spectrophotometry/spectroscopy (UV-Vis, NMR, SPR/Biacore)

 

cell culture

 

primary cultures & immortalized lines

bacterial, murine & human cultures, 2D & 3D culture techniques, ES cell differentiation to neural progenitors (embryoid body & monolayer), hybridoma creation, T-cell cloning, T-cell polarization, phages/phage display & liposomes, antigen screening (3H-T pulsing), flow cytometry (FACS), mini/midi/maxipreps (Qiagen), phage display / phage screening

 

animal models

animal husbandry

genotyping & colony maintenance, transgenic animal creation, knockout/knock-in & conditional knockout

protocols

[immunology & developmental neurology] priming, mAb studies, adoptive transfer, IP, lymph node & tail vein injections, EAE modeling & scoring, in-utero electroporation, cre system

tissue preparation & studies

perfusion, dissection & tissue collection, OCT, paraffin, & agarose embedding, sectioning & histology, H&E, hoechst, lacZ, ICS, HRP, in-situ, immunostaining/immunofluorescence, excellent microscopy skills

 

data analysis

software

Microsoft: Powerpoint, Word, Excel, FrontPage; Adobe Suite: Strong fluency with InDesign and Illustrator, proficiency with Dreamweaver; Other: Vector, Prism, GraphPad, R, Diva, FlowJo, predictive epitope algorithms (IEDB, MetaMHC), virtual molecular analysis (Chimera), HTML, comfort with Python for basic backend and analysis of larger datasets with Anaconda, NumPy, SciPy, Pandas

 

databases

creation, organization, and fluency with those such as BLAST, INSD/GenBank, Clustal, PDB, GenBank, mGen, Entrez, Swiss-Prot, UniProt, OMIM, NCBI-UniGene, and STRING

 

mathematics

data analysis through figure creation, reaction kinetics, binding/dissociation calculations, calculus, statistics & biostatistics, linear algebra, regressions, data modeling/predictive analytics, and (of course) stoichiometry. 

 

data science & machine learning

supervised learning (linear and logistic regressions, decision trees, support vector machines (SVM)) & unsupervised learning (k-means clustering, principal component analysis (PCA))

experience using random forest, data mining, neural networks, ensemble classifiers / context-dependent classification

descriptive analytics, predictive analytics, prescriptive analytics