F
Federico Minneci
Researcher at University College London
Publications - 14
Citations - 2418
Federico Minneci is an academic researcher from University College London. The author has contributed to research in topics: Protein function prediction & Medicine. The author has an hindex of 10, co-authored 11 publications receiving 2188 citations.
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Journal ArticleDOI
Isolation and Comparative Transcriptome Analysis of Human Fetal and iPSC-Derived Cone Photoreceptor Cells
Emily Welby,Jorn Lakowski,Valentina Di Foggia,Dimitri Budinger,Anai Gonzalez-Cordero,Aaron T. L. Lun,Michael Epstein,Aara Patel,Elisa Cuevas,Kamil Kruczek,Arifa Naeem,Federico Minneci,Mike Hubank,David T. Jones,John C. Marioni,John C. Marioni,Robin R. Ali,Jane C. Sowden +17 more
TL;DR: An analysis of the human L/M-opsin cone photoreceptor transcriptome using an AAV2/9.pR2.1:GFP reporter led to the identification of a cone-enriched gene signature, which was used to demonstrate similar gene expression between fetal and stem cell-derived cones.
Journal ArticleDOI
Genome3D: a UK collaborative project to annotate genomic sequences with predicted 3D structures based on SCOP and CATH domains
Tony E. Lewis,Ian Sillitoe,Antonina Andreeva,Tom L. Blundell,Daniel W. A. Buchan,Cyrus Chothia,Alison L. Cuff,Jose M. Dana,Ioannis Filippis,Julian Gough,Sarah Hunter,David T. Jones,Lawrence A. Kelley,Gerard J. Kleywegt,Federico Minneci,Alex L. Mitchell,Alexey G. Murzin,Bernardo Ochoa-Montaño,Owen J. L. Rackham,James Smith,Michael J.E. Sternberg,Sameer Velankar,Corin Yeats,Christine A. Orengo +23 more
TL;DR: The main aim of Genome3D is to enable comparisons between all the resources so that biologists can see where predictions agree and are therefore more trusted, and contains the first official mapping between these two databases.
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FFPred 2.0: improved homology-independent prediction of gene ontology terms for eukaryotic protein sequences.
TL;DR: FFPred 2.0 as mentioned in this paper uses support vector regression models for the prediction of 442 Gene Ontology (GO) terms, which largely expand the coverage of the ontology and of the biological process category in particular.
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Genome3D: exploiting structure to help users understand their sequences
Tony E. Lewis,Ian Sillitoe,Antonina Andreeva,Tom L. Blundell,Daniel W. A. Buchan,Cyrus Chothia,Domenico Cozzetto,Jose M. Dana,Ioannis Filippis,Julian Gough,David T. Jones,Lawrence A. Kelley,Gerard J. Kleywegt,Federico Minneci,Jaina Mistry,Alexey G. Murzin,Bernardo Ochoa-Montaño,Matt E. Oates,Marco Punta,Owen J. L. Rackham,Jonathan Stahlhacke,Michael J.E. Sternberg,Sameer Velankar,Christine A. Orengo +23 more
TL;DR: This work has improved the superposition tools, which now give users a more powerful interface for investigating similarities and differences between structural models.
Journal ArticleDOI
Estimation of the time course of neurotransmitter release at central synapses from the first latency of postsynaptic currents
TL;DR: Method for estimating vesicular release time course from PSC first latencies and analysis of binomial model of release at central synapses for generalization of existing first latency correction based on Poisson model.