Nina Truter

Translational Scientist, Freelance Contractor

LinkedIn: www.linkedin.com/in/nina-truter
Email: nj.truter@gmail.com

Location: Cape Town, South Africa

My mission

I am a translational scientist dedicated to advancing our understanding of disease development through the integration of diverse disciplines. I am driven to apply targeted literature and deep thinking to translate experimental and computer-generated results into insights that impact disease understanding and drug discovery and development.

I have a wealth of experience in interpreting outputs from various computational engines, experimental methods and a unique capability to navigate through diverse disease spectra. I am flexible based on the needs of the team and have worked with a range of people, from deep biologists to bioinformaticians and developers. I have handled different types of datasets, spanning across Omics and model systems, including transcriptomic, proteomic, and phenotypic data. I excel in deciphering complex biological pathways and signaling mechanisms, offering cost-effective and high quality work.

What I offer

Examples of what I do

In-depth interpretation of experimental and computational results
Comprehensive reviews of literature (including comparison of results to similar experiments), targets, molecules, disease mechanisms and clinical trials
Processing and analysis of experimental data
Discovering public data to supplement understanding of experimental results or develop initial hypotheses
Deciding on an experimental or computational method based on the scientific question
Describing impact of results for patients and recommending next steps
Writing concise reports or scientific articles to summarise results and their impact
Understanding the needs and pain points of potential customers of scientific services/tools
Effectively communicating the use of a scientific service/tool to potential customers

Projects I have worked on

I employed pathway databases, literature and the domain knowledge of QVBio's scientists to construct the biological processes potentially involved in the mechanism of action of their electric field therapy. I made decisions about how to use their proprietary in vitro intervention data for analysis. Subsequently, I interpreted the results of our analysis and wrote an in-depth report delineating the key drivers within different DNA repair pathways and programmed cell death pathways across various treatment regimes.

Impact: using key insights highlighted in my report, QVBio was able to narrow down a potential mechanism of action of their electric field therapy on glioblastoma cell lines and identify potential targets to test in the future for synergistic therapy.

Publications demonstrating translation science

Signaling pathway evaluation of leading ATRi, PARPi and CDK7i cancer compounds targeting the DNA Damage Response using Causal Inference

We utilised publicly-available, in vitro transcriptomic data to identify genes and pathways driving resistance to cancer inhibitors. We translated these genes and pathways into potential combination therapies that can be used in patients, as well as identifying specific indications and patients in which mono- and combination therapy could be effective in.

ALaSCA: a computational platform for quantifying the effect of proteins using Pearlian causal inference, with an example application in Alzheimer’s disease

We used a marker of neuronal aging (climbing ability in Drosophila) to understand the potential contribution of proteins from the S6K pathway in the decline of human neuronal function. Literature evidence revealed that the human orthologs of the proteins we identified in Drosophila were altered in the hippocampus of Alzheimer's disease patients.

Supervised machine learning with feature selection for prioritization of targets related to time-based cellular dysfunction in aging

We utilised multiple datasets describing the aging-related decline in function in C. elegans, ranging from phenotypic to molecular and Omics markers, and compared their association to transcriptomic and phosphorylation changes across the lifespan of C. elegans. We incorporated knowledge of key aging processes into the characterisation of these markers, which allowed us to describe how changes on the gene and protein phosphorylation level could affect the larger system of C. elegans. A unique post-processing workflow was established to translate the prioritised genes to pathways and cellular processes in human aging, to support their potential druggability for aging-related diseases.

Why you shouldn't be afraid of playing with someone else's data - using existing public datasets to answer your own research questions

As researchers, we typically generate hypotheses based on findings from our previous research and by trawling through literature...

njtruter

Mar 27, 20243 min read

Dr Ashwin Narayanan

Principle Scientist, QVBio

I had the pleasure of collaborating and working closely with Nina on a project using causal analysis. Nina possesses an exceptional ability to integrate findings from diverse statistical and AI methodologies, synthesizing them into coherent insights. Her proficiency in conducting comprehensive literature reviews complements her analytical skills, ensuring that every decision and conclusion is grounded in robust evidence and current scientific understanding.

Nina is a consummate professional who exhibits strong communication skills, effortlessly translating technical concepts into clear and accessible language. Her proficiency in data interpretation and commitment to staying current with research makes her an invaluable asset to any team. I enthusiastically endorse Nina and look forward to her future endeavours.

Dr Dan Leggate

Life science industry advisor

Nina has great skill in translating complicated computational analyses into useful biological insight. She communicates these findings and their relevance clearly both in oral and written presentations.

Prof Tony Sedgwick, UK

Thought Disruptor, Life science industry advisor

Nina is a real pleasure to work with . Great enthusiasm and very knowledgable.
I would very strongly recommend Nina.