Biognosys’ Head of Business Development & Sales, Ben Gonzales, recently sat down with NeoGenomics Laboratories’ Director of Scientific Affairs, Anna Juncker-Jensen, to discuss all things Biomarker Discovery. What are the biggest challenges researchers face today? And how can the collaboration between NeoGenomics and Biognosys help overcome them?

Watch the interview to hear their perspectives. To get to know more about this strategic partnership, click here.

Another episode of our SpotLight video series is out!

Let our Head of R&D LC-MS and Workflows, Roland Bruderer, guide you through discovering the fascinating world of tissue proteomics and explain how deep we can now explore the tissue proteomes to uncover enlightening insights.

Trapped ion mobility spectrometry (TIMS) extends conventional LC-MS/MS proteomic workflows with an additional ion mobility dimension. Next to the benefits of signal separation, the implementation of TIMS in Bruker timsTOF instruments has demonstrated that collisional cross section (CCS) values of peptides are highly reproducible and can be used as orthogonal coordinates to retention time and ion m/z values for targeted data extraction in data-independent acquisition (DIA) workflows, or as additional metric for rescoring in spectrum-centric database searches.

Neural networks have been extensively used in the proteomics field and their role on improving identifications is rapidly becoming more relevant. DeepiRT is a neural network designed to predict Indexed Retention Time (iRT) (Escher, 2012) for a given precursor based on its modified sequence.

This poster delves into the ULTRA-DEEP EXPLORATION OF HUMAN TISSUE PROTEOMES, where 20025 protein groups were identified across all 22 tissue samples (19 healthy and 3 cancer). The poster concludes that the qualitative human tissue digital proteome serves as a rich resource that can be mined for various applications such as basal protein expression, different proteoforms, PTMs etc.

Mass spectrometry (MS)-based proteomics allows the comprehensive identification and quantification of proteins in various biological specimen such as cell lines, body fluids or tissues. The study of these complex samples for applications like biomarker discovery requires large sample cohorts with low technical variability to overcome inter-individual differences and achieve sufficient statistical power.

Rapid developments in the field of proteomics within recent years have enabled the reproducible and reliable quantification of large sample cohorts. Large scale studies comprising hundreds of samples are primarily processed and analyzed in one centralized facility.

Advances in mass spectrometry proteomics now make it possible to achieve unprecedented depth and coverage faster than ever before. In this case study we demonstrate the advantages of our new workflow based on the Bruker timsTOF® platform, delivering unbiased high-throughput analysis of lung cancer and healthy tissue samples in less than 24 hours.

The primary goal of many DIA based experiments is to discover proteins or peptides (candidates) that are differentially expressed in two or more conditions. Improvements in DIA workflow are typically measured based on identification, precision, and accuracy.

New: Spectronaut^® 19

Unlock Your Data's True Story

New: Spectronaut^® 19

Unlock Your Data's True Story

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