Posters2s

Poster: Variation of gene expression in the liver of Nile tilapia at different time points of sub-chronic exposure to Benzo(a)pyrene

Variation of gene expression in the liver of Nile tilapia at different time points of sub-chronic exposure to Benzo(a)pyrene Nacira Anahi Albornoz-Abud,Rossana del Pilar Rodriguez-Canul,Reyna Cristina Colli-Dula Cinvestav del IPN Unidad Mérida Abstract Polycyclic aromatic hydrocarbons (PAHs) are pollutants of environmental concern because they are widely distributed in aquatic systems around the world. Although, benzo(a)pyrene (BaP) is a model PAH known for its carcinogenic effects in vertebrates, information on its molecular toxicity in aquatic organisms is still lacking.

Poster: Unraveling Immunogenomic Diversity in Single-Cell Data

Unraveling Immunogenomic Diversity in Single-Cell Data Ahmad Al Ajami,Katharina Imkeller University Hospital Frankfurt Abstract Immune molecules such as B and T cell receptors, human leukocyte antigens (HLAs), or killer Ig-like receptors (KIRs) are encoded in the genetically most diverse loci of the human genome. Many of these immune genes are hyperpolymorphic – showing high allelic diversity across human populations. In addition, typical immune molecules are polygenic, which means that multiple functionally similar genes encode the same protein subunit.

Poster: The transcriptional landscape of drug effects in CLL

The transcriptional landscape of drug effects in CLL Caroline Lohoff,Junyan Lu Heidelberg University Hospital, Lu Group Abstract Despite extensive investigation of appropriate drugs for the treatment of CLL, the resulting transcriptional response remain incompletely understood. In this collaboration with the University Hospital Zurich and GeneCore we investigate the transcriptional landscape of drug effects in chronic lymphocytic leukemia (CLL) in a systematic and high-throughput manner. The data set consists of more than 1100 low depth 3‘-end RNAseq samples from more than 100 patients.

Poster: ProFaNA - Neighborhood analysis for prediction of gene function

ProFaNA - Neighborhood analysis for prediction of gene function Bartosz Baranowski,Krzysztof Pawłowski Institute of Biochemistry and Biophysics, Polish Academy of Sciences Abstract Many genes in microbial genomes remain functionally uncharacterized. Understanding signaling and metabolic pathways involving such genes is essential for deeper understanding of microbial biology and also mechanisms of infectious diseases. It is well known that groups of genes neighboring in the genome are more likely to share similar biological functions than random pairs of genes.

Poster: PeptidoformViz is a shiny app for processing, visualising and analysing mass spectrometry based intensity data on peptidoform level

PeptidoformViz is a shiny app for processing, visualising and analysing mass spectrometry based intensity data on peptidoform level Nina Demeulemeester,Lien Provez,Laura Corveleyn,Bart Van Puyvelde,Lennart Martens,Maarten Dhaenens,Lieven Clement Ghent University - VIB Abstract Many histones are known to carry a plethora of post-translational modifications (PTMs)(1). Changes in these histone PTMs (hPTMs) have been linked to a variety of diseases (2). Nonetheless, the mapping of hPTMs, with the aid of mass spectrometry based proteomics (MS) has not been extensively described.

Poster: miaSim: a time series simulation R package for microbial ecology

miaSim: a time series simulation R package for microbial ecology Yagmur Simsek,Yu Gao,Daniel Rios Garza,Karoline Faust,Leo M Lahti Department of Computing, University of Turku, Finland Abstract Hundreds to thousands of species interact in natural microbial communities. Computer simulations in microbiome ecology are therefore becoming increasingly important to understand the interactions between species. In this script, we introduce miaSim: a time series tool to simulate microbiome ecology, a new open-source, publicly available R package modelling microbial population dynamics in a repeatable, transparent, and scalable manner.

Poster: Means to visualize spatial patterns in host-associated microbiome data

Means to visualize spatial patterns in host-associated microbiome data Ida Holopainen,Matti Ruuskanen,Leo M Lahti,Aki Havulinna Finnish Institute for Health and Welfare Abstract Host-associated microbial communities are affected by ecological processes, living environment, diet, and health status of the host organism. Because many of these factors display spatial patterns, they can also create spatial variation in the microbiome compositions between hosts. To date, there are only few studies that have investigated such spatial patterns in host-associated microbiomes.

Poster: EMMA - Enrichment Methods Matter

EMMA - Enrichment Methods Matter Federico Marini,Annekathrin Silvia Ludt University Medical Center Mainz Abstract Functional enrichment analysis, performed either via scripted analysis or with web-based tools, is one of the most frequently adopted steps in computational biology, especially when identifying the systems level mechanisms captured by high-dimensional molecular datasets. Recent work (Wijesooriya et al. 2022 - doi: 10.1371/journal.pcbi.1009935) showed that, despite their popularity, methodological issues (e.g. the use of inappropriate background for enrichment, or the lack of detail provided in the Materials and Methods section) might undermine the validity and reproducibility of many research endeavors using (incorrectly) such methods.

Poster: CytoPipeline: building and visualizing automated pre-processing and quality control pipelines for flow cytometry data

CytoPipeline: building and visualizing automated pre-processing and quality control pipelines for flow cytometry data Philippe Hauchamps,Dan Lin,Laurent Gatto Computation Biology and Bioinformatics (CBIO) Unit, de Duve Institute, UCLouvain, Belgium Abstract With the increase of the dimensionality in conventional flow cytometry data over the past years, there is a growing need to replace or complement traditional manual analysis (i.e. iterative 2D gating) with automated data analysis pipelines. Examples of such pipelines have been documented in the recent literature (e.

Poster: Comparison of two methods for deteting diffferential expression in a RNA-seq Tilapia study

Comparison of two methods for deteting diffferential expression in a RNA-seq Tilapia study Reyna Cristina Colli-Dula,Nacira Anahi Albornoz-Abud Cinvestav del IPN Unidad Mérida Abstract Benzo(a)pyrene (BaP) is a hydrocarbon present in aquatic systems derived from various anthropogenic activities. This compound can be bioaccumulated in aquatic organisms of economic importance and because it is considered carcinogenic and mutagenic, it may present adverse effects on the development of reproductive organs. Therefore, its early detection is important at the molecular level in aquatic organisms using RNA-sequencing (RNA-seq) omic techniques, which have revolutionized the characterization of changes in their transcriptome.

Poster: A corpus of standardized CITE-seq data

A corpus of standardized CITE-seq data Bernat Bramon Mora,Helen Lindsay,Raphael Gottardo Biomedical Data Science Center at the Lausanne University Hospital (CHUV) Abstract Cell type annotation is one of the central challenges in single-cell analyses, a necessary step for biological interpretation and downstream statistical analyses. While a lot of progress has been made to this date, current state-of-the-art techniques still suffer from major limitations, including lack of ground truth, reliance on limited reference datasets, and lack of standard annotations.