Riccardo Percudani

Irena Maus (ELIXIR-DE) with Integrating ELIXIR Germany Within the European Infrastructure closes a stimulating Elixir All-Hands meeting in Bari @elixir-it.bsky.social

Deeply saddened by the passing of Amos Bairoch, a true pioneer of bioinformatics and biological databases. His contributions shaped our field.
www.sib.swiss/news/amos-ba...

Urate metabolism, in the gut url: academic.oup.com/lifemeta/art...

Eukaryotic tree showing coevolution of CatSper subunits

A new component of the CatSper ion channel identified!
Great collaboration with Jean-Ju Chung (Yale School of Medicine) and Jianping Wu (Westlake University).
www.nature.com/articles/s41...

Profylo: A Python Package for Phylogenetic Profile Comparison and Analysis https://pubmed.ncbi.nlm.nih.gov/41160131/

Analyzing RL components for Wagner’s framework via Brouwer’s conjecture - Machine Learning In this work, we continue the study and systematization started in our previous work (Angileri et al. in: Lecture notes in computer science 15243 LNAI, 2025, pp 325–338. https://doi.org/10.1007/978-3-031-78977-9_21 ) of Wagner’s Reinforcement Learning framework to investigate graph conjectures. After identifying three main directions that impact the framework’s performance (the environment dynamics, the RL algorithm and the neural network used as a function approximator), we conduct an ablation study to evaluate the effectiveness of each component, analyzing several variations of them. The experiments compare three environment dynamics, implemented as Gym spaces (Linear, Local and Global), two algorithms [PPO and the Cross-Entropy method (Wagner in Constructions in combinatorics via neural networks, 2021, https://arxiv.org/abs/2104.14516 )], different neural network structures (Multi-Layer Perceptron and Graph Neural Networks) and reward systems. This study was intended not only to test the framework’s capabilities, but also to identify a configuration of environment, algorithm, and neural network that can be effective when exploring graph spaces, even with a complex target. For this reason, all the experiments were executed on Brouwer’s Conjecture. We also present the data collected with the various trained models, as these interesting configurations can be used in the inference process on the problem. Our analysis shows that a proper calibration of the individual components of the framework can significantly improve its performance, suggesting effective settings for addressing complex problems and contributing to the study of Brouwer’s Conjecture. All the codes and data are open source and available at https://github.com/CuriosAI/graph_conjectures .

Great new machine learning study from @unipr researchers
Read it here 👉 doi.org/10.1007/s109...

Michael Galperin is a wizard.

Using bioinformatics for identifying and plugging metabolic pathway holes | PNAS Using bioinformatics for identifying and plugging metabolic pathway holes

Using bioinformatics for identifying and plugging metabolic pathway holes | PNAS www.pnas.org/doi/10.1073/...

The activity and expression of adenylosuccinate lyase were reduced during modern human evolution, affecting brain and behavior | PNAS www.pnas.org/doi/10.1073/...

Coevolution in human metabolism

We used coevolutionary analysis of KEGG networks to identify the gene linked to L-xylulose formation in human metabolism and Garrod's pentosuria.
#Bioinformatics #Genomics #Biochemistry

Now in PNAS: t.co/iPIhrbUmxz
(Preprint: www.researchsquare.com/article/rs-6...)

Structural variation in human genome based on pangenome analysis. Tobias Marschall at #ISMBECCB2025

Charlotte Dean on the future of AI-driven drug discovery #ISMBECCB2025 key note

Erva Ulusoy presenting ProtHGT: protein function prediction using biological knowledge graphs and LLM at #ISMBECCB2025

Clara De Paolis Kaluza on the past, present, and future of CAFA at #ISMBECCB2025

Matthias Blum: integrating AI in InterPro. #ismbeccb2025 function COSI

Erik Sonnhammer nicely presenting the FunCoup database and the complexity of functional networks at the #Ismbeccb2025

Nicola Bordin: novel domain arrangements but no novel folds in the metagenome billion-scale protein universe. Nicely reported at the #ismbeccb2025

Paul D. Thomas illustrating the GO annotation as derived from evolutionary modeling at #ismbeccb2025

The birth and death of protein domains in metazoa presented by Maureen Stolzer at the #ismbeccb2025 functon-evolution section

Marc Robinson-Rechavi, the funcional divergence of orthologs and paralogs, and the Bgee database at the function-EvolCompBiol section of #ismbeccb2025

Overton prize James Zou illuminating the future of computational biology in his #ismbeccb2025 keynote on AI agents.

Adam Gudys presenting at the EvolCompgen section of #ISMBECCB2025 FAMSA2: protein multiple alignment at the protein universe scale

Amos Bairoch resuming 45 y of #biocuration in his #ISMBECCB2025 keynote

Janet Thornton introducing John Jumper for the opening keynote at #ismbeccb2025

I'm participating the ISMB/ECCB 2025 conference, join me! Register now

I'm attending #ISMBECCB2025 in Liverpool, United Kingdom from July 20-24. Who else is going? Register here and don't miss it! invt.io/1bxbsd8t5hg

Predicting Protein Function in the AI and Big Data Era It is an exciting time for researchers working to link proteins to their functions. Most techniques for extracting functional information from genomic sequences were developed several years ago, with ...

Predicting Protein Function in the AI and Big Data Era | Biochemistry pubs.acs.org/doi/10.1021/...

EvoWeaver: large-scale prediction of gene functional associations from coevolutionary signals www.nature.com/articles/s41... 🧬🖥️🧪 #Rstats bioconductor.org/packages/Syn...

Allantoin - In 1800, Vauquelin, together with Buniva, discovered a substance present in cow amniotic fluid but not in that of humans. It was later found in allantoic fluid and named allantoin. Allantoin is the end product of purine degradation in placental mammals, but not in humans and other apes

Malic acid - Vauquelin confirmed the existence of malic acid, which he isolated from apple juice. This intermediate of the Krebs and glyoxylate cycles was first discovered by Carl Wilhelm Scheele and later named by Antoine Lavoisier after the Latin word for apple, malum.

Asparagine - In 1806, Louis Nicolas Vauquelin and his assistant Pierre Jean Robiquet isolated asparagine (Asn, N) in crystalline form. As the first of the 20 universal amino acids to be identified, asparagine was named after its source: asparagus juice.