Titlebook: Research in Computational Molecular Biology; 28th Annual Internat Jian Ma Conference proceedings 2024 The Editor(s) (if applicable) and The

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,Sequential Optimal Experimental Design of?Perturbation Screens Guided by?Multi-modal Priors,nference of gene circuits, the discovery of therapeutic targets and the reprogramming and engineering of cells. In recent years, Perturb-seq, pooled genetic screens with single cell RNA-seq (scRNA-seq) readouts, has emerged as a common method to collect such data. Despite technological advancements,

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,Efficient Analysis of?Annotation Colocalization Accounting for?Genomic Contexts,fications. A common task is to compare two annotations to determine if one is enriched or depleted in the regions covered by the other. We study the problem of assigning statistical significance to such a comparison based on a null model representing two random unrelated annotations. To incorporate

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,FragXsiteDTI: Revealing Responsible Segments in?Drug-Target Interaction with?Transformer-Driven Intmance. We propose a novel transformer-based model, FragXsiteDTI, that aims to address these challenges in DTI prediction. Notably, FragXsiteDTI is the first DTI model to simultaneously leverage drug molecule fragments and protein pockets. Our information-rich representations for both proteins and dr

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,An Integer Programming Framework for?Identifying Stable Components in?Asynchronous Boolean Networks In particular, Boolean network models have been a prime research focus and dozens of manually curated Boolean models are available in public databases. A key challenge in studying the dynamics of these models is determining their asymptotic behavior, that is the state-sets or attractors they conver

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ImputeCC Enhances Integrative Hi-C-Based Metagenomic Binning Through Constrained Random-Walk-Based tating the reconstruction of high-quality metagenome-assembled genomes (MAGs) from complex microbial communities. However, current Hi-C-based contig binning methods solely depend on Hi-C interactions between contigs to group them, ignoring invaluable biological information, including the presence of

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