James Evans
@evansrjames
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Postdoctoral research fellow at UCL Queen Square Institute of Neurology and the Francis Crick Institute. Former musician.
London
Joined April 2020
Very excited to share our latest work published in @NatMachIntell. We used ipsc-derived neurons, high-throughout imaging, and machine learning approaches to predict Parkinson’s disease subtypes. https://t.co/g4R6L6adgo
nature.com
Nature Machine Intelligence - Deep learning applied to live-cell images of patient-derived neurons aids predicting underlying mechanisms and gains insights into neurodegenerative diseases,...
The @LabGandhi team took part in an intensive coding course when the pandemic disrupted their research – and now they’ve published work with @faculty_ai showing that computer models can classify types of Parkinson’s from images of stem cells 🧠 @UCLIoN
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Out now on biorxiv! Excited to share our latest collaborative work investigating the earliest stages of Parkinson’s disease. https://t.co/CFDoYmYHq4 Thanks to all the amazing co-authors Melissa Grant-Peters Joseph Beckwith Steven Lee Mina Ryten @LabGandhi
biorxiv.org
Parkinson’s disease (PD) is characterised by insoluble α-synuclein (αSyn) aggregates in Lewy bodies (LBs) within the substantia nigra, with cortical pathology appearing as the disease progresses....
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Microglial activation and alpha-synuclein oligomers drive the early inflammatory phase of Parkinson's disease https://t.co/fMXb8hElqQ
#biorxiv_neursci
biorxiv.org
Parkinson’s disease (PD) is characterised by insoluble α-synuclein (αSyn) aggregates in Lewy bodies (LBs) within the substantia nigra, with cortical pathology appearing as the disease progresses....
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VP-CLEM-Kit: An accessible pipeline for visual proteomics using super resolution volume correlative light and electron microscopy ... https://t.co/OxbydQPeZk
#biorxiv_cellbio
biorxiv.org
Visual proteomics (VP) aims to allow researchers to visualise, measure and analyse proteins in the context of cell and tissue structure in health and disease. VP is becoming a reality through...
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Really exciting to be involved with this work! Congrats @EM_STP and team!
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New research suggests nonlysosomal roles for #Parkinsons-associated GBA1 & its highly homologous pseudogene GBAP1 "with implications for our understanding of the role of GBA1 in health & disease" - from @em_ka_gu et al; Concealment of GBA1 by GBAP1 https://t.co/1aooz5W3Q6
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Finally in print! I really think there is more to this "pseudo"gene. This has been such a nice collaborative effort and am really grateful to all that has been part of this story @ASAP_Research @PD_BrainMap @PD_Progression @ATransposons #GBA1 #GBAP1 #PD
science.org
Long-read RNA sequencing uncovers unexpected protein-coding roles for GBA1 and GBAP1, exhibiting tissue and cell type selectivity.
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Exciting multiscale post-doc opportunity in #Parkinsons @WCHN_UCL & @TheCrick: Combining individual specific cell models @LabGandhi with longitudinal qMRI in the same person to define mechanisms of progression See link for details: https://t.co/cuuFkBDsiL
@OHBM #OHBM2024
ucl.ac.uk
UCL is consistently ranked as one of the top ten universities in the world (QS World University Rankings 2010-2022) and is No.2 in the UK for research power (Research Excellence Framework 2021).
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In dopamine neurons, 10% of SNCA expression encodes novel open reading frames. Understanding the 3' UTRstructures enabled targeted ASO design, reversing key PD pathologies. #Parkinsons #SNCA #ASO
biorxiv.org
The role of the SNCA gene locus in driving Parkinson’s disease (PD) through rare and common genetic variation is well-recognized, but the transcriptional diversity of SNCA in vulnerable cell types...
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Very surreal to see THE TOWER pictured inside Barnes & Noble on Fifth Avenue 🏰🗽 Thank you for the photos, @evansrjames
#TheTower #MaryQueenOfScots @BNBuzz
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A friend of mine is in San Francisco and paid a visit to the iconic independent bookstore @citylightsbooks… and spotted THE TOWER inside! 🏰 The shop is a city landmark and known for publishing Allen Ginsberg's ‘Howl’.
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Combined small-molecule treatment accelerates maturation of human pluripotent stem cell-derived neurons | Nature Biotechnology
nature.com
Nature Biotechnology - Neurons derived from stem cells are rapidly matured with a GENtoniK cocktail.
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Head spinning after a brilliant morning at the Francis Crick Institute meeting Prof Sonia Gandhi and her team who are mapping the Parkinson’s brain.
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Machine learning can accurately predict subtypes of Parkinson’s disease using images of patient-derived stem cells, reports a study published in @NatMachIntell. https://t.co/E6bjsjPlqj
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"We now hope to expand this approach to understand how these cellular mechanisms contribute to other subtypes of Parkinson’s." James Evans @evansrjames (@UCLIoN) on a new study involving @LabGandhi and the @TheCrick. Read in @Independent ⬇️
independent.co.uk
The findings could pave the way for personalised medicine and targeted drug discovery, researchers have said.
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Machine learning can accurately predict subtypes of Parkinson’s disease using images of patient-derived stem cells, finds a new study by researchers at UCL and the Francis Crick Institute. @LabGandhi @evansrjames @UCLIoN @TheCrick Read more ⬇️
ucl.ac.uk
Machine learning can accurately predict subtypes of Parkinson’s disease using images of patient-derived stem cells, finds a new study by researchers at UCL and the Francis Crick Institute.
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A great collaborative effort from @LabGandhi @GurvirVirdi @DilanAthauda @MineeChoi @faculty_ai @MathewHHorrocks @EdBiophysics
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We're learning more about Parkinson's disease through innovative #AI research💡 Our Life Sciences team is working with @TheCrick and @ucl Institute of Neurology to use #machinelearning to accurately predict subtypes of Parkinson’s disease based on stem cells images.👇
The @LabGandhi team took part in an intensive coding course when the pandemic disrupted their research – and now they’ve published work with @faculty_ai showing that computer models can classify types of Parkinson’s from images of stem cells 🧠 @UCLIoN
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Machine learning on patient cells can accurately classify subtypes of Parkinson's, which could open the door to personalised medicine, finds research by PhD candidate James Evans @evansrjames & Prof Sonia Gandhi @LabGandhi @UCLIoN @TheCrick
ucl.ac.uk
Machine learning can accurately predict subtypes of Parkinson’s disease using images of patient-derived stem cells, finds a new study by researchers at UCL and the Francis Crick Institute.
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