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Jeremy Parker

dblp:64/5128 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › single-cell analysis
cytometry data analysis
0.212015
Deep profiling of multitube flow cytometry data · Bioinform. 2015
Bioinformatics and computational biology
immunophenotyping
0.212015
Deep profiling of multitube flow cytometry data · Bioinform. 2015

Methods — techniques the papers use, named apart from their topics

nearest-neighbour imputation · 0.2clustering · 0.2classification · 0.2
YearPublicationVenuePosition
2024 V-Band Power Amplifier MMIC Cell Implemented in GaAs
abstract
A versatile compact power-amplifier cell for rapid development of V-band GaAs MMICs is reported. It was designed using a single-finger, non-linear model with an EM simulation of the interconnect. In a small active area of 1.8 mm2, the cell offers 30.1 dB power gain over the 58–66 GHz band. The versatility for rapid development is demonstrated by assembling various amplifiers: two cells in parallel, a full-balanced amplifier with four cells, and a transceiver MMIC using a single-cell as the transmitter and a half-cell as the receiver. For these variants output power is 27.3, 29.3, 19.6 dBm at 1-dB gain compression, and 29.8, 29.9, 27.3 dBm in saturation respectively.
Jeremy Parker, Simon J. Mahon, Andrew J. Jones, Syed Muzahir Abbas
TENCON1
2015 Deep profiling of multitube flow cytometry data
abstract
Abstract Motivation: Deep profiling the phenotypic landscape of tissues using high-throughput flow cytometry (FCM) can provide important new insights into the interplay of cells in both healthy and diseased tissue. But often, especially in clinical settings, the cytometer cannot measure all the desired markers in a single aliquot. In these cases, tissue is separated into independently analysed samples, leaving a need to electronically recombine these to increase dimensionality. Nearest-neighbour (NN) based imputation fulfils this need but can produce artificial subpopulations. Clustering-based NNs can reduce these, but requires prior domain knowledge to be able to parameterize the clustering, so is unsuited to discovery settings. Results: We present flowBin, a parameterization-free method for combining multitube FCM data into a higher-dimensional form suitable for deep profiling and discovery. FlowBin allocates cells to bins defined by the common markers across tubes in a multitube experiment, then computes aggregate expression for each bin within each tube, to create a matrix of expression of all markers assayed in each tube. We show, using simulated multitube data, that flowType analysis of flowBin output reproduces the results of that same analysis on the original data for cell types of >10% abundance. We used flowBin in conjunction with classifiers to distinguish normal from cancerous cells. We used flowBin together with flowType and RchyOptimyx to profile the immunophenotypic landscape of NPM1-mutated acute myeloid leukemia, and present a series of novel cell types associated with that mutation. Availability and implementation: FlowBin is available in Bioconductor under the Artistic 2.0 free open source license. All data used are available in FlowRepository under accessions: FR-FCM-ZZYA, FR-FCM-ZZZK and FR-FCM-ZZES. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Kieran O'Neill, Nima Aghaeepour, Jeremy Parker, Donna Hogge, Aly Karsan, Bakul Dalal, Ryan Remy Brinkman
Bioinform.3