SLAS Technology

Papers
(The H4-Index of SLAS Technology is 16. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-05-01 to 2025-05-01.)
ArticleCitations
Automation of the Whole-Blood Thiopurine S-Methyltransferase (TPMT) Phenotyping Assay Using the Biomek NXP and Biomek i5 Liquid-Handling Workstations75
Incorporation of automated buffer exchange empowers high-throughput protein and plasmid purification for downstream uses62
In vitro delivery of mTOR inhibitors by kidney-targeted micelles for autosomal dominant polycystic kidney disease51
Automated measurement of transepithelial electrical resistance (TEER) in 96-well transwells using ECIS TEER96: Single and multiple time point assessments45
Creating Custom Digital Assistants for the Scientific Laboratory using the HelixAI Platform37
Multiplex digital microfluidics using serial controls and its applications in glucose sensing36
High-throughput mass spectrometry in drug discovery33
High-throughput differential scanning fluorimetry (DSF) and cellular thermal shift assays (CETSA): Shifting from manual to automated screening33
Evaluation of the Use of Cold Plasma for Microtiter Plate Cleaning to Reduce Plastic Biohazard Waste29
Publisher's note28
Employing synthetic biology to expand antibiotic discovery26
Development of a novel, automated, robotic system for rapid, high-throughput, parallel, solid-phase peptide synthesis25
Deciphering the role of heat shock protein HSPA1L: biomarker discovery and prognostic insights in Parkinson's disease and glioma22
Fully automated extraction of high-quality total nucleic acids from FFPE specimens for comprehensive genomic profiling of solid tumors20
A microfluidic model for infantile in vitro digestions: Characterization of lactoferrin digestion20
Integrating NLP and LLMs to discover biomarkers and mechanisms in Alzheimer's disease18
Development and validation of automated methods for COVID-19 PCR Master Mix preparation16
Assessment and classification of COVID-19 DNA sequence using pairwise features concatenation from multi-transformer and deep features with machine learning models16
Disease Modeling with 3D Cell-Based Assays Using a Novel Flowchip System and High-Content Imaging16
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