Judit kumuthini

Dr. Judit kumuthini


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 April 2022 in Human Genetics
Verified
Journal Article
Open access
PDF file
JKJudit kumuthini
Judit kumuthini
BZBrittany Zick
Brittany Zick
ABAngeliki Balasopoulou
Angeliki Balasopoulou
CCConstantina Chalikiopoulou
Constantina Chalikiopoulou
Collet DandaraCollet Dandara
Collet Dandara
MAMarc Abramowicz
Marc Abramowicz
Genomic medicine aims to improve health using the individual genomic data of people to inform care. While clinical utility of genomic medicine in many monogenic, Mendelian disorders is amply demonstrated, clinical utility is less evident in polygenic traits, e.g., coronary artery disease or breast cancer. Polygenic risk scores (PRS) are subsets of individual genotypes designed to capture heritability of common traits, and hence to allow the stratification of risk of the trait in a population. We systematically reviewed the PubMed database for unequivocal evidence of clinical utility of polygenic risk scores, using stringent inclusion and exclusion criteria. While we identified studies demonstrating clinical validity in conditions where medical intervention based on a PRS is likely to benefit patient outcome, we did not identify a single study demonstrating unequivocally such a benefit, i.e. clinical utility. We conclude that while the routine use of PRSs hold great promise, translational research is still needed before they should enter mainstream clinical practice.

26 March 2020 in PLOS Computational Biology
Verified
Journal Article
Open access
PDF file
JKJudit kumuthini
Judit kumuthini
MCMichael Chimenti
Michael Chimenti
SNSven Nahnsen
Sven Nahnsen
APAlexander Peltzer
Alexander Peltzer
RMRebone Meraba
Rebone Meraba
LZLyndon Zass
Lyndon Zass
Life scientists are increasingly turning to high-throughput sequencing technologies in their research programs, owing to the enormous potential of these methods. In a parallel manner, the number of core facilities that provide bioinformatics support are also increasing. Notably, the generation of complex large datasets has necessitated the development of bioinformatics support core facilities that aid laboratory scientists with cost-effective and efficient data management, analysis, and interpretation. In this article, we address the challenges—related to communication, good laboratory practice, and data handling—that may be encountered in core support facilities when providing bioinformatics support, drawing on our own experiences working as support bioinformaticians on multidisciplinary research projects. Most importantly, the article proposes a list of guidelines that outline how these challenges can be preemptively avoided and effectively managed to increase the value of outputs to the end user, covering the entire research project lifecycle, including experimental design, data analysis, and management (i.e., sharing and storage). In addition, we highlight the importance of clear and transparent communication, comprehensive preparation, appropriate handling of samples and data using monitoring systems, and the employment of appropriate tools and standard operating procedures to provide effective bioinformatics support. The article we wrote draws from our experience in core support facilities and highlights 10 best practices that individuals who apply information technology approaches to biological, medical, and health research should consider when providing support to individuals who generate data for this research in the lab. As interdisciplinary approaches are increasingly being utilized within the biological and medical sciences, effective collaboration and support between the aforementioned parties is crucial to promote the quality and integrity of research. These practices highlight the importance of quality control, comprehensive reporting, effective communication, and more in the production of quality data as well as the promotion of effective collaboration.

1 January 2025 in NEJM AI
Verified
Journal Article
Closed access
JAJoseph E. Alderman
Joseph E. Alderman
JPJoanne Palmer
Joanne Palmer
ELElinor Laws
Elinor Laws
MMMelissa D. McCradden
Melissa D. McCradden
JOJohan Ordish
Johan Ordish
XLXiaoxuan Liu
Xiaoxuan Liu

9 December 2021 in PLOS Computational Biology
Verified
Journal Article
Open access
PDF file
SAShaun Aron
Shaun Aron
CJC. Victor Jongeneel
C. Victor Jongeneel
PCPaballo Abel Chauke
Paballo Abel Chauke
MCMelek Chaouch
Melek Chaouch
JKJudit kumuthini
Judit kumuthini
NMNicola Mulder
Nicola Mulder

30 December 2019 in BMC Bioinformatics
Verified
Journal Article
Open access
PDF file
JKJudit kumuthini
Judit kumuthini
LZLyndon Zass
Lyndon Zass
SPSumir Panji
Sumir Panji
SSSamson P. Salifu
Samson P. Salifu
JKJonathan K. Kayondo
Jonathan K. Kayondo
NMNicola J. Mulder
Nicola J. Mulder
Background: Currently, formal mechanisms for bioinformatics support are limited. The H3Africa Bioinformatics Network has implemented a public and freely available Helpdesk (HD), which provides generic bioinformatics support to researchers through an online ticketing platform. The following article reports on the H3ABioNet HD (H3A-HD)‘s development, outlining its design, management, usage and evaluation framework, as well as the lessons learned through implementation. Results: The H3A-HD evaluated using automatically generated usage logs, user feedback and qualitative ticket evaluation. Evaluation revealed that communication methods, ticketing strategies and the technical platforms used are some of the primary factors which may influence the effectivity of HD. Conclusion: To continuously improve the H3A-HD services, the resource should be regularly monitored and evaluated. The H3A-HD design, implementation and evaluation framework could be easily adapted for use by interested stakeholders within the Bioinformatics community and beyond.

11 February 2022 in Journal of Personalized Medicine
Verified
Journal Article
Open access
PDF file
HOHoucemeddine Othman
Houcemeddine Othman
LZLyndon Zass
Lyndon Zass
JRJorge E. B. da Rocha
Jorge E. B. da Rocha
Fouzia RadouaniFouzia Radouani
Fouzia Radouani
CSChaimae Samtal
Chaimae Samtal
Samar Kamal KassimSamar Kamal Kassim
Samar Kamal Kassim
Genomics data are currently being produced at unprecedented rates, resulting in increased knowledge discovery and submission to public data repositories. Despite these advances, genomic information on African-ancestry populations remains significantly low compared with European- and Asian-ancestry populations. This information is typically segmented across several different biomedical data repositories, which often lack sufficient fine-grained structure and annotation to account for the diversity of African populations, leading to many challenges related to the retrieval, representation and findability of such information. To overcome these challenges, we developed the African Genomic Medicine Portal (AGMP), a database that contains metadata on genomic medicine studies conducted on African-ancestry populations. The metadata is curated from two public databases related to genomic medicine, PharmGKB and DisGeNET. The metadata retrieved from these source databases were limited to genomic variants that were associated with disease aetiology or treatment in the context of African-ancestry populations. Over 2000 variants relevant to populations of African ancestry were retrieved. Subsequently, domain experts curated and annotated additional information associated with the studies that reported the variants, including geographical origin, ethnolinguistic group, level of association significance and other relevant study information, such as study design and sample size, where available. The AGMP functions as a dedicated resource through which to access African-specific information on genomics as applied to health research, through querying variants, genes, diseases and drugs. The portal and its corresponding technical documentation, implementation code and content are publicly available.