UniProt: the Universal Protein Knowledgebase in 2023

Database resources of the National Center for Biotechnology Information: update

Wheeler, D. L. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh073 · Cited by 10,695

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

Varadi, M., Anyango, S., Deshpande, M., Nair, S., Natassia, C., Yordanova, G., Yuan, D., Stroe, O., Wood, G., Laydon, A., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1061 · Cited by 7,850 · cited 1×

UniProt: the universal protein knowledgebase in 2021

The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1100 · Cited by 6,372

Database resources of the national center for biotechnology information

Sayers, E. W., Bolton, E. E., Brister, J. R., Canese, K., Chan, J., Comeau, D. C., Connor, R., Funk, K., Kelly, C., Kim, S., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1112 · Cited by 2,812

InterPro in 2022

Paysan‐Lafosse, T., Blum, M., Chuguransky, S., Grego, T., Pinto, B. L., Salazar, G. A., Bileschi, M. L., Bork, P., Bridge, A. J., Colwell, L. J., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac993 · Cited by 2,457

Ensembl 2022

Cunningham, F., Allen, J. E., Allen, J., Alvarez-Jarreta, J., Amode, M. R., Armean, I. M., Austine-Orimoloye, O., Azov, A. G., Barnes, I., Bennett, R., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1049 · Cited by 1,923

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences

Burley, S. K., Bhikadiya, C., Bi, C., Bittrich, S., Chen, L., Crichlow, G. V., Christie, C. H., Dalenberg, K., Di Costanzo, L., Duarte, J. M., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1038 · Cited by 1,581

ChEBI in 2016: Improved services and an expanding collection of metabolites

Hastings, J., Owen, G., Dekker, A., Ennis, M., Kale, N., Muthukrishnan, V., Turner, S., Swainston, N., Mendes, P., & Steinbeck, C. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1031 · Cited by 1,083

Metabolomics: A New Tool to Reveal the Nature of Diabetic Kidney Disease

Huang, G., Li, M., Li, Y. J., & Mao, Y. (2022) · Laboratory Medicine · doi:10.1093/labmed/lmac041 · Cited by 933

BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions

Yang, J., Roy, A., & Zhang, Y. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks966 · Cited by 749

SoIR: a comprehensive Solanaceae information resource for comparative and functional genomic study

Liu, Z., Shen, S., Li, C., Zhang, C., Chen, X., Fu, Y., Yu, T., Zhou, R., Liu, D., Yang, Q., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1040 · Cited by 26

Analysis of 1386 epileptogenic brain lesions reveals association with DYRK1A and EGFR

Boßelmann, C. M., Leu, C., Brünger, T., Hoffmann, L., Baldassari, S., Chipaux, M., Coras, R., Kobow, K., Hamer, H. M., Delev, D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54911-w · Cited by 27

Machine Learning in nanoarchitectonics

Parakhonskiy, B. V., Song, J., & Skirtach, A. G. (2025) · Advances in Colloid and Interface Science · doi:10.1016/j.cis.2025.103546 · Cited by 27

Using Machine Learning to Fast-Track Peptide Nanomaterial Discovery

Dražić, E., Jelušić, D., Janković, P., Mauša, G., & Kalafatović, D. (2025) · ACS Nano · doi:10.1021/acsnano.5c00670 · Cited by 31

Transcriptomic profiling of the medicinal plant Clitoria ternatea: identification of potential genes in cyclotide biosynthesis

Kalmankar, N. V., Venkatesan, R., Balaram, P., & Sowdhamini, R. (2020) · Scientific Reports · doi:10.1038/s41598-020-69452-7 · Cited by 26

How AlphaFold2 shaped the structural coverage of the human transmembrane proteome

Jambrich, M. A., Tusnády, G., & Dobson, L. (2023) · Scientific Reports · doi:10.1038/s41598-023-47204-7 · Cited by 27

The 2023 Report on the Proteome from the HUPO Human Proteome Project

Omenn, G. S., Lane, L., Overall, C. M., Lindskog, C., Pineau, C., Packer, N. H., Cristea, I. M., Weintraub, S. T., Orchard, S. E., Roehrl, M. H. A., et al. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00591 · Cited by 30

pyrpipe : a Python package for RNA-Seq workflows

Singh, U., Li, J., Seetharam, A. S., & Wurtele, E. S. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab049 · Cited by 26

Asgard archaea reveal the conserved principles of ESCRT-III membrane remodeling

Souza, D. P., Espadas, J., Chaaban, S., Moody, E. R. R., Hatano, T., Balasubramanian, M., Williams, T. A., Roux, A., & Baum, B. (2025) · Science Advances · doi:10.1126/sciadv.ads5255 · Cited by 30

Paenibacillus polymyxa YLC1 : a promising antagonistic strain for biocontrol of Pseudomonas syringae pv. actinidiae , causing kiwifruit bacterial canker

Wang, H., Wang, N., Tan, Y., Mi, Q., Mao, Y., Zhao, C., Tian, X., Liu, W., & Huang, L. (2023) · Pest Management Science · doi:10.1002/ps.7633 · Cited by 25

Haplotype-Resolved, Chromosome-Level Assembly of White Clover (Trifolium repens L., Fabaceae)

Santangelo, J. S., Battlay, P., Hendrickson, B. T., Kuo, W., Olsen, K. M., Kooyers, N. J., Johnson, M. T. J., Hodgins, K. A., & Ness, R. W. (2023) · Genome Biology and Evolution · doi:10.1093/gbe/evad146 · Cited by 25

An N terminomics toolbox combining 2-pyridinecarboxaldehyde probes and click chemistry for profiling protease specificity

Bridge, H. N., Leiter, W. E., Frazier, C. L., & Weeks, A. M. (2023) · Cell chemical biology · doi:10.1016/j.chembiol.2023.09.009 · Cited by 25

Accurate and Fast Prediction of Intrinsically Disordered Protein by Multiple Protein Language Models and Ensemble Learning

Xu, S., & Onoda, A. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c01202 · Cited by 26

Nucleolus activity-dependent recruitment and biomolecular condensation by pH sensing

Aryan, F., Detrés, D., Luo, C. C., Kim, S. X., Shah, A. N., Bartusel, M., Flynn, R. A., & Calo, E. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.10.031 · Cited by 25

PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins

Marrama, D., Chronister, W. D., Westernberg, L., Vita, R., Koşaloğlu‐Yalçın, Z., Sette, A., Nielsen, M., Greenbaum, J., & Peters, B. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05606-4 · Cited by 25

Tick hemocytes have a pleiotropic role in microbial infection and arthropod fitness

Rolandelli, A., Laukaitis-Yousey, H. J., Bogale, H. N., Singh, N., Samaddar, S., O’Neal, A. J., Ferraz, C. R., Butnaru, M., Mameli, E., Xia, B., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46494-3 · Cited by 25

Architecture and regulation of filamentous human cystathionine beta-synthase

McCorvie, T. J., Adamóski, D., Machado, R. A. C., Tang, J., Bailey, H., Ferreira, D. S. M., Strain-Damerell, C. M., Baslé, A., Ambrosio, A. L. B., Dias, S. M. G., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46864-x · Cited by 25

Paeoniflorin inhibits the inflammation of rheumatoid arthritis fibroblast-like synoviocytes by downregulating hsa_circ_009012

Yang, J., Wei, Z., Li, H., Lv, S., Fu, Y., & Xiao, L. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e30555 · Cited by 27

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Schroeder, W. L., Suthers, P. F., Willis, T. C., Mooney, E. J., & Maranas, C. D. (2024) · Metabolites · doi:10.3390/metabo14070365 · Cited by 26

MAGEL2 (patho‐)physiology and Schaaf–Yang syndrome

Schubert, T., & Schaaf, C. P. (2024) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.16018 · Cited by 25

Structures prediction and replica exchange molecular dynamics simulations of α-synuclein: A case study for intrinsically disordered proteins

Coskuner‐Weber, O. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.133813 · Cited by 26

Exploring the Antioxidant and Anti-Inflammatory Potential of Saffron (Crocus sativus) Tepals Extract within the Circular Bioeconomy

Frusciante, L., Geminiani, M., Shabab, B., Olmastroni, T., Scavello, G., Rossi, M., Mastroeni, P., Nyong’a, C. N., Salvini, L., Lamponi, S., et al. (2024) · Antioxidants · doi:10.3390/antiox13091082 · Cited by 25

Effective analysis of thyroid toxicity and mechanisms of acetyltributyl citrate using network toxicology, molecular docking, and machine learning strategies

Lan, Y., Peng, Q., Fu, B., & Liu, H. (2024) · Toxicology · doi:10.1016/j.tox.2024.154029 · Cited by 25

Teaching AI to speak protein

Heinzinger, M., & Rost, B. (2025) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2025.102986 · Cited by 27

Large language models open new way of AI-assisted molecule design for chemists

Ishida, S., Sato, T., Honma, T., & Terayama, K. (2025) · Journal of Cheminformatics · doi:10.1186/s13321-025-00984-8 · Cited by 29

Prediction of protein subcellular localization in single cells

(2025) · doi:10.1038/s41592-025-02696-1 · Cited by 25

MDCrow: automating molecular dynamics workflows with large language models

Campbell, Q., Cox, S., Medina, J., Watterson, B., & White, A. (2026) · Machine Learning Science and Technology · doi:10.1088/2632-2153/ae4b07 · Cited by 68

Brain abnormalities, neurodegeneration, and dysosteosclerosis (BANDDOS): new cases, systematic literature review, and associations with CSF1R-ALSP

Dulski, J., Souza, J., Santos, M. L. S. F., & Wszołek, Z. K. (2023) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-023-02772-9 · Cited by 26

Deciphering sources of PET signals in the tumor microenvironment of glioblastoma at cellular resolution

Bartos, L. M., Kirchleitner, S. V., Kolabas, Z. I., Quach, S., Beck, A., Lorenz, J., Blobner, J., Müller, S. A., Ulukaya, S., Hoeher, L., et al. (2023) · Science Advances · doi:10.1126/sciadv.adi8986 · Cited by 25

A protein sequence-based deep transfer learning framework for identifying human proteome-wide deubiquitinase-substrate interactions

Liu, Y., Li, D., Zhang, X., Xia, S., Qu, Y., Li, Y., Li, Y., Kong, X., Zhang, L., Cui, C.-P., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48446-3 · Cited by 24

Structure-based prediction of protein-nucleic acid binding using graph neural networks

Sagendorf, J. M., Mitra, R., Huang, J., Chen, X. S., & Rohs, R. (2024) · Biophysical Reviews · doi:10.1007/s12551-024-01201-w · Cited by 26

A comprehensive dataset of protein-protein interactions and ligand binding pockets for advancing drug discovery

Moine-Franel, A., Mareuil, F., Nilges, M., Ciambur, C. B., & Spérandio, O. (2024) · Scientific Data · doi:10.1038/s41597-024-03233-z · Cited by 25

The evolutionary origins and ancestral features of septins

Delic, S., Shuman, B., Lee, S., Bahmanyar, S., Momany, M., & Onishi, M. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1406966 · Cited by 22

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets

Xu, X., Khunsriraksakul, C., Eales, J., Rubin, S., Scannali, D., Saluja, S., Talavera, D., Markus, H., Wang, L., Drzal, M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46132-y · Cited by 26

Bioactive peptides derived from the enzymatic hydrolysis of cowhide collagen for the potential treatment of atherosclerosis: A computational approach

Hamadou, M., Başaran, B., Mune, M. A. M., Abubakar, A. M., Nandwa, J. O., Raimi, M. Z. K. A., & Hashmi, M. Z. (2024) · Intelligent Pharmacy · doi:10.1016/j.ipha.2024.05.004 · Cited by 24

Chemoproteomic profiling of substrate specificity in gut microbiota-associated bile salt hydrolases

Han, L., Pendleton, A., Singh, A., Xu, R., Scott, S. A., Palma, J. A., Diebold, P. J., Malarney, K. P., Brito, I., & Chang, P. V. (2024) · Cell chemical biology · doi:10.1016/j.chembiol.2024.05.009 · Cited by 26

Effects of Essential Oils on Biological Characteristics and Potential Molecular Targets in Spodoptera frugiperda

Oliveira, J. A. D. C., Fernandes, L. A., de Figueiredo, K. G., Corrêa, E. J. A., de Lima, L. H. F., Alves, D. S., Bertolucci, S. K. V., & Carvalho, G. A. (2024) · Plants · doi:10.3390/plants13131801 · Cited by 24

AI-driven antibody design with generative diffusion models: current insights and future directions

He, X., Li, J.-R., Xu, J., Shan, H., Shen, S.-Y., Gao, S.-H., & Xu, H. E. (2024) · Acta Pharmacologica Sinica · doi:10.1038/s41401-024-01380-y · Cited by 28

Pathogenic proteotoxicity of cryptic splicing is alleviated by ubiquitination and ER-phagy

Prieto‐Garcia, C., Matković, V., Mosler, T., Li, C., Liang, J., Oo, J. A., Haidle, F., Mačinković, I., Cabrera‐Orefice, A., Berkane, R., et al. (2024) · Science · doi:10.1126/science.adi5295 · Cited by 24

Ensemble deep learning model for protein secondary structure prediction using NLP metrics and explainable AI

Vignesh, U., Parvathi, R., & Ram, K. G. (2024) · Results in Engineering · doi:10.1016/j.rineng.2024.103435 · Cited by 25

From discovery to application: Enabling technology-based optimizing carbonyl reductases biocatalysis for active pharmaceutical ingredient synthesis

Gu, J., Mu, W., Xu, Y., & Nie, Y. (2024) · Biotechnology Advances · doi:10.1016/j.biotechadv.2024.108496 · Cited by 27

Unipept in 2024: Expanding Metaproteomics Analysis with Support for Missed Cleavages and Semitryptic and Nontryptic Peptides

Moortele, T. V., Devlaminck, B., de Vyver, S. V., Bossche, T. V. D., Martens, L., Dawyndt, P., Mesuere, B., & Verschaffelt, P. (2025) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00848 · Cited by 24

Synapsin Condensation is Governed by Sequence-Encoded Molecular Grammars

Hoffmann, C., Ruff, K. M., Edu, I. A., Shinn, M. K., Tromm, J. V., King, M. R., Pant, A., Ausserwöger, H., Morgan, J. R., Knowles, T. P. J., et al. (2025) · Journal of Molecular Biology · doi:10.1016/j.jmb.2025.168987 · Cited by 27

Phosphoproteomic Analysis of CARMIL1 Reveals Novel Regulatory Mechanisms and Upstream Kinases Involved in Actin Dynamics and Cell Migration

Sheela, A., Mahin, A., Ummar, S., Vattoth, N. N., Dcunha, L., Gopalakrishnan, A. P., & Raju, R. (2025) · Cytoskeleton · doi:10.1002/cm.70001 · Cited by 24

Co-folding, the future of docking – prediction of allosteric and orthosteric ligands

Nittinger, E., Yoluk, Ö., Tibo, A., Olanders, G., & Tyrchan, C. (2025) · Artificial Intelligence in the Life Sciences · doi:10.1016/j.ailsci.2025.100136 · Cited by 35

Hollow Octadecameric Self-Assembly of Collagen-like Peptides

Yu, L. T., Hancu, M. C., Kreutzberger, M. A. B., Henrickson, A., Demeler, B., Egelman, E. H., & Hartgerink, J. D. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.2c12931 · Cited by 25

The role of prickle proteins in vertebrate development and pathology

Radaszkiewicz, K., Šulcová, M., Kohoutkova, E., & Harnoš, J. (2023) · Molecular and Cellular Biochemistry · doi:10.1007/s11010-023-04787-z · Cited by 17

Alternative Splicing, RNA Editing, and the Current Limits of Next Generation Sequencing

Piazzi, M., Bavelloni, A., Salucci, S., Faenza, I., & Blalock, W. L. (2023) · Genes · doi:10.3390/genes14071386 · Cited by 24

A class of secreted mammalian peptides with potential to expand cell-cell communication

Wiggenhorn, A. L., Abuzaid, H. Z., Voilquin, L., Li, V. L., Tanzo, J. T., Wei, W., Lyu, X., Svensson, K. J., & Long, J. Z. (2023) · Nature Communications · doi:10.1038/s41467-023-43857-0 · Cited by 27

Structural basis of Cfr-mediated antimicrobial resistance and mechanisms to evade it

Aleksandrova, E. V., Wu, K. J. Y., Tresco, B. I. C., Syroegin, E. A., Killeavy, E. E., Balasanyants, S. M., Svetlov, M. S., Gregory, S. T., Atkinson, G. C., Myers, A. G., et al. (2024) · Nature Chemical Biology · doi:10.1038/s41589-023-01525-w · Cited by 26

Single-Cell Analyses Offer Insights into the Different Remodeling Programs of Arteries and Veins

Rojas, M. G., Pereira‐Simon, S., Zigmond, Z. M., Santos, J. V., Perla, M., Falcon, N. S., Stoyell‐Conti, F. F., Salama, A., Yang, X., Long, X., et al. (2024) · Cells · doi:10.3390/cells13100793 · Cited by 27

Involvement of the choroid plexus in Alzheimer’s disease pathophysiology: findings from mouse and human proteomic studies

Delvenne, A., Vandendriessche, C., Gobom, J., Burgelman, M., Dujardin, P., Nolf, C. D., Tijms, B. M., Teunissen, C. E., Schindler, S. E., Verhey, F. R. J., et al. (2024) · Fluids and Barriers of the CNS · doi:10.1186/s12987-024-00555-3 · Cited by 27

Identification of highly conserved, serotype-specific dengue virus sequences: implications for vaccine design

Chong, L. C., & Khan, A. M. (2019) · BMC Genomics · doi:10.1186/s12864-019-6311-z · Cited by 25

Growth Mode and Physiological State of Cells Prior to Biofilm Formation Affect Immune Evasion and Persistence of Staphylococcus aureus

Savijoki, K., Miettinen, I., Nyman, T. A., Kortesoja, M., Hanski, L. L., Varmanen, P., & Fallarero, A. (2020) · Microorganisms · doi:10.3390/microorganisms8010106 · Cited by 23

Attractor Concepts to Evaluate the Transcriptome-wide Dynamics Guiding Anaerobic to Aerobic State Transition in Escherichia coli

Bui, T. T., & Selvarajoo, K. (2020) · Scientific Reports · doi:10.1038/s41598-020-62804-3 · Cited by 20

ECMpy 2.0: A Python package for automated construction and analysis of enzyme-constrained models

Mao, Z., Niu, J., Zhao, J., Huang, Y., Wu, K., Yun, L., Guan, J., Yuan, Q., Liao, X., Wang, Z., et al. (2024) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2024.04.005 · Cited by 25

Insight into Janus kinases specificity: From molecular architecture to cancer therapeutics

Wei, T., Lu, M., Yao, S., Hong, Y., Yang, J., Zhang, M., Yin, Y., Han, Y., Li, Q., Wang, Z., et al. (2024) · MedComm – Oncology · doi:10.1002/mog2.69 · Cited by 22

Calcifying Odontogenic Cyst Demonstrates Recurrent WNT Pathway Mutations and So-Called Adenoid Ameloblastoma-Like Histology: Evidence Supporting Its Classification as a Neoplasm

Oh, K., Kim, J.-H., & Yoon, H. (2024) · Modern Pathology · doi:10.1016/j.modpat.2024.100484 · Cited by 24

Fibrillar extracellular matrix produced by pericyte‐like cells facilitates glioma cell dissemination

Výmola, P., Garcia‐Borja, E., Červenka, J., Balážiová, E., Výmolová, B., Vepřková, J., Vodička, P., Skalníková, H. K., Tomáš, R., Netuka, D., et al. (2024) · Brain Pathology · doi:10.1111/bpa.13265 · Cited by 24

Maintenance of bacterial outer membrane lipid asymmetry: insight into MlaA

Kaur, M., & Mingeot-Leclercq, M. P. (2024) · BMC Microbiology · doi:10.1186/s12866-023-03138-8 · Cited by 26

Using EMBL‐EBI Services via Web Interface and Programmatically via Web Services

Madeira, F., Madhusoodanan, N., Lee, J., Eusebi, A., Niewielska, A., Tivey, A. R., Meacham, S., López, R., & Butcher, S. (2024) · Current Protocols · doi:10.1002/cpz1.1065 · Cited by 23

Human gut microbes express functionally distinct endoglycosidases to metabolize the same N-glycan substrate

Sastre, D. E., Sultana, N. A., Navarro, M. V. A. S., Huličiak, M., Du, J. J., Cifuente, J. O., Flowers, M. W., Liu, X., Lollar, P., Trastoy, B., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48802-3 · Cited by 24

Genome-scale exon perturbation screens uncover exons critical for cell fitness

Xiao, M., Damodaran, A. P., Kumari, B., Dickson, E., Xing, K., On, T. A., Parab, N., King, H. E., Perez, A. R., Guiblet, W. M., et al. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.05.024 · Cited by 23

Algal methylated compounds shorten the lag phase of Phaeobacter inhibens bacteria

Sperfeld, M., Narváez‐Barragán, D. A., Malitsky, S., Frydman, V., Yuda, L., Rocha, J., & Segev, E. (2024) · Nature Microbiology · doi:10.1038/s41564-024-01742-6 · Cited by 24

Unveiling the potential: Extracellular vesicles from plant cell suspension cultures as a promising source

Kırbaş, O. K., Sağraç, D., Ciftci, C., Özdemir, G., Öztürkoğlu, D., Bozkurt, B. T., Derman, Ü. C., Taşkan, E., Taşlı, P. N., Özdemir, B. S., et al. (2024) · BioFactors · doi:10.1002/biof.2090 · Cited by 23

Molecular mimicry in the pathogenesis of autoimmune rheumatic diseases

Fehringer, M., & Vogl, T. J. (2025) · Journal of Translational Autoimmunity · doi:10.1016/j.jtauto.2025.100269 · Cited by 26

Quality and composition control of complex TCM preparations through a novel “Herbs-in vivo Compounds-Targets-Pathways” network methodology: The case of Lianhuaqingwen capsules

Chen, S., Qi, H., Zhu, C., Zhao, Y., Jiao, B., Tan, Y., Yuexin, Y., Wang, T., Hou, Y., Dai, B., et al. (2025) · Pharmacological Research · doi:10.1016/j.phrs.2025.107650 · Cited by 23

RBM43 controls PGC1α translation and a PGC1α-STING signaling axis

Dumesic, P. A., Wilensky, S. E., Bose, S., Vranken, J. G. V., Gygi, S. P., & Spiegelman, B. M. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2025.01.013 · Cited by 28

Advancing the Identification of Bioactive Molecules and the Construction of a Synergistic Drug Delivery System in Combating Lung Injury

Qi, J., Wang, Y., Chen, H., Wu, K., Zhou, P., Dou, Y., Xiong, B., & Zhou, W. (2025) · Advanced Science · doi:10.1002/advs.202407802 · Cited by 23

Unravelling the phosphoregulatory network of protein kinase C-delta (PKC-δ)

Raghu, D. H., Dcunha, L., Ahmed, M., Fahma, A., Mahin, A., Gopalakrishnan, A. P., John, L., Subair, S., Shivamurthy, P. B., Varghese, S., et al. (2025) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2025.141080 · Cited by 23

Toxicity of true-to-life microplastics to human iPSC-derived intestinal epithelia correlates to their protein corona composition

Brouwer, H., Busch, M., Yang, S., Venus, T., Aalderink, G., de Ferrer, J. A., Villacorta, A., Hernández, A., Estrela‐Lopis, I., Boeren, S. A., et al. (2025) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2025.138908 · Cited by 28

BroadAMP-GPT: AI-Driven generation of broad-spectrum antimicrobial peptides for combating multidrug-resistant ESKAPE pathogens

Li, Y., Xu, X., Zhang, X., Xu, Z., Zhao, J., Zhu, R., Wang, Z., Ran, W., Zhao, W., Yan, N., et al. (2025) · Gut Microbes · doi:10.1080/19490976.2025.2523811 · Cited by 28

De novo design of a peptide modulator to reverse sodium channel dysfunction linked to cardiac arrhythmias and epilepsy

Mahling, R. W., Hegyi, B., Cullen, E. R., Cho, T. M., Rodriques, A., Fossier, L., Yehya, M., Yang, L., Chen, B.-X., Katchman, A. N., et al. (2025) · Cell · doi:10.1016/j.cell.2025.07.038 · Cited by 27

Structure and dynamics of Toll immunoreceptor activation in the mosquito Aedes aegypti

Saucereau, Y., Wilson, T. H., Tang, M. C. K., Moncrieffe, M. C., Hardwick, S. W., Chirgadze, D. Y., Soares, S. G., Marcaida, M. J., Gay, N. J., & Gangloff, M. (2022) · Nature Communications · doi:10.1038/s41467-022-32690-6 · Cited by 20

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Tang, S., Cui, X., Wang, R., Li, S., Li, S., Huang, X., & Chen, S. (2024) · Nature Communications · doi:10.1038/s41467-024-46045-w · Cited by 23

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Wu, C. H., Apweiler, R., Bairoch, A., Natale, D. A., Barker, W. C., Boeckmann, B., Ferro, S., Gasteiger, E., Huang, H., López, R., et al. (2005)