Read about how researchers across the world are using QIAGEN Digital Insights solutions to accelerate their work in a variety of applications
Making sense of complex ‘omics data, and developing the infrastructure to compile, store, search, analyze and visualize relevant information has significant challenges and may pose a burden to researchers without bioinformatics skills. Yet powerful insights derived from ‘omics data help innovate, integrate and translate scientific results into impactful discoveries. Many noteworthy papers cite QIAGEN Digital Insights solutions and demonstrate how our tools help drive research insights and discoveries. These papers use QIAGEN Ingenuity Pathway Analysis (IPA), QIAGEN CLC and/or QIAGEN OmicSoft to help drive success. The QIAGEN Digital Insights portfolio encompasses a comprehensive, easy-to-use toolbox that ensures continuity in the NGS workflow. Here, we have curated a selection of just a few recent papers to offer a sense of the diversity of the research for which QIAGEN Digital Insights solutions makes a difference.
First author: Yuki Shibayama
Did you know on average pancreatic cancer patients acquire over 67 non-synonymous mutations? The team at Kagawa University used QIAGEN IPA to study the role of (pro)renin receptor [(P)RR] in causing genomic instability. Read their full paper here.
First author: Katerina Lawlor
Did you know cancer cells are not only good at proliferating but can also suppress other cells from growing? See how the team at Imperial College London investigates this phenomenon using QIAGEN IPA to understand how cancer cells induce quiescence in glioblastomas. Read their full paper here.
Multiparametric profiling of engineered nanomaterials: Unmasking the surface coating effect
First author: Audrey Gallud
Discover this fascinating research by scientists at the Karolinska Institutet who study the cytotoxic effects of engineered nanomaterials (ENMs). See how the team uses QIAGEN IPA to understand the mechanism behind the cytotoxic effects of ENMs and how to mitigate the risks. Read the full article here.
Innate immune training of granulopoiesis promotes anti-tumor activity
First author: Lydia Kalafati
Check out this exciting research by L. Kalafati and colleagues at TU Dresden, who try to promote the anti-tumor activity of trained neutrophils. See how the team uses QIAGEN IPA to understand the molecular mechanism behind reprogramming caused by trained immunity agonists. Read the paper here.
First author: Richard J. P. Brown
Did you know the hepatitis C virus (HCV) affects 71 million people worldwide but only infects humans? Read how researchers at Paul Ehrlich Institute (PEI) use QIAGEN IPA and QIAGEN CLC Genomics Workbench to understand how mice are able to prevent HCV infection. Read their full paper here.
Vascular disease and thrombosis in SARS-CoV-2-infected rhesus macaques
First author: Malika Aid
Is there a connection between thrombosis and SARS-CoV-2 infection? Read how the team at Beth Israel Deaconess Medical Center uses QIAGEN IPA to understand the critical interactions between various pathways that lead to SARS-CoV-2-induced blood clotting in rhesus macaques. Read their full paper here.
First author: Benjamin Meckiff
Check out this critical coronavirus research by B. Meckiff and colleagues at the La Jolla Institute for Immunology, who study the role of CD4+ T cells in COVID-19. See how the team uses QIAGEN IPA to understand how different subsets of CD4+ T cells play a role in pathogenic immune responses to SARS-CoV-2 infection. Read the full article here.
First author: Michael R. Garvin
Can mutations in coronavirus spike proteins help it escape current vaccines? See how a group at Oak Ridge National Laboratory predicts mutational hotspots in the viral genome using QIAGEN CLC Genomics and AI models. Read the full article here.
Co-author: Joel Sevinsky
Is SARS-COV-2 reinfection possible? Joel Sevinsky and his colleagues in the Nevada public health arena report the first SARS-Cov-2 reinfection case in the US. See how the team uses QIAGEN CLC Genomics Workbench for bioinformatics analysis of their SARS-CoV-2 samples to discover whether it was the same virus or a genetically different specimen. Read the full article here.
Two distinct immunopathological profiles in autopsy lungs of COVID-19
First author: Ronny Nienhold
Is unlocking differences in immune response the key to treating ARDS in COVID-19? Dig into this important coronavirus research from R. Nienhold and colleagues at Cantonal Hospital Baselland who study different immunopathological profiles in COVID-19 patients. See how the team uses QIAGEN CLC Genomics Workbench to understand the different immune patterns observed in post mortem COVID-19 lung tissue. See their full article here.
First author: Sarah R. Leist
Did you know coronaviruses are responsible for three epidemics in the 21st century? Great work by S. Leist and colleagues at the University of North Carolina at Chapel Hill, who created a mouse-adapted SARS-CoV-2 to understand the virus better. See how the team uses QIAGEN CLC Genomics Workbench to characterize this animal model and discover mechanisms for SARS-CoV-2 pathogenesis to test potential therapeutics. Read their full paper here.
First author: Lori Garman
Single-cell analysis improves our understanding of multimodal diseases. Don’t miss this exciting cancer research by L. Garman and colleagues, who study the role of immune cells in sarcoidosis. The team uses QIAGEN IPA and QIAGEN OmicSoft DiseaseLand to identify dysregulated pathways using single-cell analysis. Read the full paper here.
First author: Catarina Chaves
Congratulations to the researchers at Sanofi for publishing their findings on a comparative model for the human blood-brain barrier (hBBB). See how the team uses QIAGEN IPA and QIAGEN OmicSoft Studio to investigate the transcriptome of brain capillaries from a non-human primate, and compare it to the hBBB. Read the full paper here.
Preclinical validation of therapeutic targets predicted by tensor factorization on heterogeneous graphs
First author: Saee Paliwal
Do we need better models for validating preclinical drug target candidates? How can we test these models? Read how researchers at BenevolentAI use QIAGEN OmicSoft DiseaseLand to evaluate the robustness of their computational model, Rosalind. Read the full paper here.
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