Related papers: MOSGA: Modular Open-Source Genome Annotator
RNA plays a pivotal role in diverse biological processes, ranging from gene regulation to catalysis. Recent advances in RNA design, such as RfamGen, Ribodiffusion and RDesign, have demonstrated promising results, with successful designs of…
Genome sequence analysis, which examines the DNA sequences of organisms, drives advances in many critical medical and biotechnological fields. Given its importance and the exponentially growing volumes of genomic sequence data, there are…
In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation. However, keeping track of these annotations to ensure a high-quality multi-purpose data set is a…
This study tasckles the problem of many-objective sequence optimization for semi-automated robotic disassembly operations. To this end, we employ a many-objective genetic algorithm (MaOGA) algorithm inspired by the Non-dominated Sorting…
Community annotation of biological entities with concepts from multiple bio-ontologies has created large and growing repositories of ontology-based annotation data with embedded implicit relationships among orthogonal ontologies.…
Antimony is a high-level, human-readable text-based language designed for defining and sharing models in the systems biology community. It enables scientists to describe biochemical networks and systems using a simple and intuitive syntax.…
Rosetta is a science platform for resource-intensive, interactive data analysis which runs user tasks as software containers. It is built on top of a novel architecture based on framing user tasks as microservices - independent and…
NACSOS is a web-based platform for curating data used in systematic maps. It contains several (experimental) features that aid the evidence synthesis process from finding and ingesting primary data (mainly scientific publications), basic…
De novo genome assembly is the process of stitching short DNA sequences to generate longer DNA sequences, without using any reference sequence for alignment. It enables high-throughput genome sequencing and thus accelerates the discovery of…
We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps…
Mask-based annotation of medical images, especially for 3D data, is a bottleneck in developing reliable machine learning models. Using minimal-labor user interactions (UIs) to guide the annotation is promising, but challenges remain on best…
In the past decade, transcriptome data have become an important component of many phylogenetic studies. Phylogenetic studies now regularly include genes from newly sequenced transcriptomes, as well as publicly available transcriptomes and…
DNA cytosine methylation is a critical epigenetic mark regulating gene expression and thus playing an important role in development and differentiation across eukaryotes. Existing tools for high-throughput methylation analysis often lack…
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The DOME recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for key aspects such as data…
Molecular function is largely determined by structure. Accurately aligning molecular structure with natural language is therefore essential for enabling large language models (LLMs) to reason about downstream chemical tasks. However, the…
Weak labeling is a popular weak supervision strategy for Named Entity Recognition (NER) tasks, with the goal of reducing the necessity for hand-crafted annotations. Although there are numerous remarkable annotation tools for NER labeling,…
Hierarchical models are a powerful tool for high-throughput data with a small to moderate number of replicates, as they allow sharing information across units of information, for example, genes. We propose two such models and show its…
\texttt{rCOSA} is a software package interfaced to the R language. It implements statistical techniques for clustering objects on subsets of attributes in multivariate data. The main output of COSA is a dissimilarity matrix that one can…
Radiology reports contain rich clinical information that can be used to train imaging models without relying on costly manual annotation. However, existing approaches face critical limitations: rule-based methods struggle with linguistic…
The advent of next-generation sequencing (NGS) technologies enables researchers to sequence complex microbial communities directly from environment. Since assembly typically produces only genome fragments, also known as contigs, instead of…