Publications by Sahand Jamal Rahi

Automated plasmid design for marker-free genome editing in budding yeast

Marco Labagnara, Sahand Jamal Rahi, Vojislav Gligorovski

Scarless genome editing in budding yeast with elimination of the selection marker has many advantages. Some markers such as URA3 and TRP1 can be recycled through counterselection. This permits seamless genome modification with pop-in/pop-out, in which a DN ...

OXFORD UNIV PRESS INC2025

Minimal shuttle vectors for Saccharomyces cerevisiae

Patrick Daniel Barth, Sahand Jamal Rahi

Sophisticated genetic engineering tasks such as protein domain grafting and multi-gene fusions are hampered by the lack of suitable vector backbones. In particular, many restriction sites are in the backbone outside the polylinker region (multiple cloning ...

Oxford University Press (OUP)2025

A simplified version of rapid susceptibility testing of bacteria and yeasts using optical nanomotion detection

Sandor Kasas, María Inés Villalba, Sahand Jamal Rahi, Vojislav Gligorovski

We present a novel optical nanomotion-based rapid antibiotic and antifungal susceptibility test. The technique consisted of studying the effects of antibiotics or antifungals on the nanometric scale displacements of bacteria or yeasts to assess their sensi ...

Frontiers Media SA2024

The multimodality cell segmentation challenge: toward universal solutions

Xin Yang, Bo Wang, Yixin Wang, Jun Ma, Lin Han, Maxime Emmanuel Scheder, Marco Labagnara, Sahand Jamal Rahi, Vojislav Gligorovski, Yao Zhang

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

Nature Portfolio2024

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Sahand Jamal Rahi, Kseniia Korchagina

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Portfolio2023

Personalized predictions of adverse side effects of the COVID-19 vaccines

Sahand Jamal Rahi, Nahal Mansouri

Background: Misconceptions about adverse side effects are thought to influence public acceptance of the Coronavirus disease 2019 (COVID-19) vaccines negatively. To address such perceived disadvantages of vaccines, a novel machine learning (ML) approach was ...

ELSEVIER SCI LTD2023

Inferring how animals deform improves cell tracking

Sahand Jamal Rahi

Tracking cells is a time-consuming part of biological image analysis, and traditional manual annotation methods are prohibitively laborious for tracking neurons in the deforming and moving Caenorhabditis elegans brain. By leveraging machine learning to dev ...

2023

CenFind: a deep-learning pipeline for efficient centriole detection in microscopy datasets

Pierre Gönczy, Georgios Hatzopoulos, Sahand Jamal Rahi, Martin Weigert

BackgroundHigh-throughput and selective detection of organelles in immunofluorescence images is an important but demanding task in cell biology. The centriole organelle is critical for fundamental cellular processes, and its accurate detection is key for a ...

BMC2023

Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor

Sahand Jamal Rahi, Vojislav Gligorovski

The ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr, GALL, MET3pr, CUP1pr, PHO5pr, tetOpr, terminator-tetOpr, Z(3)EV, blue-light inducible optogenetic sys ...

Nature Portfolio2023

Using optogenetics to dissect the signals maintaining the DNA damage checkpoint

Marco Labagnara, Sahand Jamal Rahi

AMER SOC CELL BIOLOGY2023

The optimal strategy balancing risk and speed predicts DNA damage checkpoint override times

Sahand Jamal Rahi

Cells have built-in mechanisms for checking for errors during replication, but these checkpoints can slow down reproduction. A theory accounting for optimal checkpoint strategies is presented and tested against observations in budding yeast. Checkpoints ar ...

2022

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Sahand Jamal Rahi, Nahal Mansouri

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...

FRONTIERS MEDIA SA2022

Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning

Sahand Jamal Rahi, Nahal Mansouri

Background: Early prediction of symptoms and mortality risks for COVID-19 patients would improve healthcare outcomes, allow for the appropriate distribution of healthcare resources, reduce healthcare costs, aid in vaccine prioritization and self-isolation ...

FRONTIERS MEDIA SA2021

Symptom Prediction and Mortality Risk Calculation for COVID-19 Using Machine Learning

Sahand Jamal Rahi, Nahal Mansouri

EUROPEAN RESPIRATORY SOC JOURNALS LTD2021

Using Machine Learning to Predict mortality for first-day COVID-19 patients presenting to the ICU

Sahand Jamal Rahi, Nahal Mansouri

EUROPEAN RESPIRATORY SOC JOURNALS LTD2021

A convolutional neural network segments yeast microscopy images with high accuracy

Nicola Dietler, Matthias Minder, Ahmad Sadeghi, Mateusz Kozinski, Sahand Jamal Rahi, Vojislav Gligorovski, Anne-Florence Raphaëlle Bitbol, Martin Weigert

The identification of cell borders ('segmentation') in microscopy images constitutes a bottleneck for large-scale experiments. For the model organism Saccharomyces cerevisiae, current segmentation methods face challenges when cells bud, crowd, or exhibit i ...

Nature Research2020