Amino Acid Difference Formula to Help Explain Protein Evolution

Evolution of the genetic code

Woese, C. R. (1973) · The Science of Nature · doi:10.1007/bf00592854 · Cited by 141

MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform

Katoh, K. (2002) · Nucleic Acids Research · doi:10.1093/nar/gkf436 · Cited by 17,027

PAML 4: Phylogenetic Analysis by Maximum Likelihood

Yang, Z. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm088 · Cited by 13,879

A general framework for estimating the relative pathogenicity of human genetic variants

Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183

A draft sequence of the Neandertal genome

Green, R. E., Krause, J., Briggs, A. W., Maricic, T., Stenzel, U., Kircher, M., Patterson, N., Li, H., Zhai, W., Fritz, M. H.-Y., et al. (2010) · Science · doi:10.1126/science.1188021 · Cited by 4,318

CADD: predicting the deleteriousness of variants throughout the human genome

Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J., & Kircher, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1016 · Cited by 3,534

De novo mutations revealed by whole-exome sequencing are strongly associated with autism

Sanders, S. J., Murtha, M. T., Gupta, A. R., Murdoch, J. D., Raubeson, M. J., Willsey, A. J., Ercan-Sencicek, A. G., DiLullo, N. M., Parikshak, N. N., Stein, J. L., et al. (2012) · Nature · doi:10.1038/nature10945 · Cited by 2,084

A codon-based model of nucleotide substitution for protein-coding DNA sequences.

(1994) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040153 · Cited by 1,960

A chromosome-based draft sequence of the hexaploid bread wheat ( Triticum aestivum ) genome

The International Wheat Genome Sequencing Consortium (IWGSC), Mayer, K. F. X., Rogers, J., Doležel, J., Pozniak, C., Eversole, K., Feuillet, C., Gill, B., Friebe, B., Lukaszewski, A. J., et al. (2014) · Science · doi:10.1126/science.1251788 · Cited by 1,583

Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease

Botstein, D., & Risch, N. (2003) · Nature Genetics · doi:10.1038/ng1090 · Cited by 1,503

Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations

O'Roak, B. J., Deriziotis, P., Lee, C., Vives, L., Schwartz, J. J., Girirajan, S., Karakoc, E., MacKenzie, A. P., Ng, S. B., Baker, C., et al. (2011) · Nature Genetics · doi:10.1038/ng.835 · Cited by 1,203

Candidate-gene approaches for studying complex genetic traits: practical considerations

Tabor, H. K., Risch, N. J., & Myers, R. M. (2002) · Nature Reviews Genetics · doi:10.1038/nrg796 · Cited by 1,076

Identification of deleterious mutations within three human genomes

Chun, S., & Fay, J. C. (2009) · Genome Research · doi:10.1101/gr.092619.109 · Cited by 1,049

Phylogeny Estimation and Hypothesis Testing Using Maximum Likelihood

Huelsenbeck, J. P., & Crandall, K. A. (1997) · Annual Review of Ecology and Systematics · doi:10.1146/annurev.ecolsys.28.1.437 · Cited by 1,018

A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome.

(1994) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040152 · Cited by 920

Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition

Litchfield, K., Reading, J. L., Puttick, C., Thakkar, K., Abbosh, C., Bentham, R., Watkins, T. B. K., Rosenthal, R., Biswas, D., Rowan, A., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.002 · Cited by 893

The Human Gene Mutation Database: 2008 update

Stenson, P. D., Mort, M., Ball, E. V., Howells, K., Phillips, A. D., Thomas, N. S., & Cooper, D. N. (2009) · Genome Medicine · doi:10.1186/gm13 · Cited by 873

ACMG recommendations for standards for interpretation and reporting of sequence variations: Revisions 2007

Richards, C. S., Bale, S., Bellissimo, D. B., Das, S., Grody, W. W., Hegde, M. R., Lyon, E., & Ward, B. E. (2008) · Genetics in Medicine · doi:10.1097/gim.0b013e31816b5cae · Cited by 832

De novo germline and postzygotic mutations in AKT3, PIK3R2 and PIK3CA cause a spectrum of related megalencephaly syndromes

Finding of Rare Disease Genes (FORGE) Canada Consortium, Rivière, J.-B., Mirzaa, G. M., O'Roak, B. J., Beddaoui, M., Alcantara, D., Conway, R. L., St-Onge, J., Schwartzentruber, J. A., Gripp, K. W., et al. (2012) · Nature Genetics · doi:10.1038/ng.2331 · Cited by 741

A systematic, large-scale resequencing screen of X-chromosome coding exons in mental retardation

Tarpey, P. S., Smith, R., Pleasance, E., Whibley, A., Edkins, S., Hardy, C., O'Meara, S., Latimer, C., Dicks, E., Menzies, A., et al. (2009) · Nature Genetics · doi:10.1038/ng.367 · Cited by 603

Spatial and Temporal Mapping of De Novo Mutations in Schizophrenia to a Fetal Prefrontal Cortical Network

Gulsuner, S., Walsh, T., Watts, A. C., Lee, M. K., Thornton, A. M., Casadei, S., Rippey, C., Shahin, H., Braff, D., Cadenhead, K. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.06.049 · Cited by 536

CATH: increased structural coverage of functional space

Sillitoe, I., Bordin, N., Dawson, N., Waman, V. P., Ashford, P., Scholes, H. M., Pang, C. S. M., Woodridge, L., Rauer, C., Sen, N., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1079 · Cited by 509

De novo gene mutations highlight patterns of genetic and neural complexity in schizophrenia

Xu, B., Ionita-Laza, I., Roos, J. L., Boone, B., Woodrick, S., Sun, Y., Levy, S., Gogos, J. A., & Karayiorgou, M. (2012) · Nature Genetics · doi:10.1038/ng.2446 · Cited by 442

A Systematic Genetic Assessment of 1,433 Sequence Variants of Unknown Clinical Significance in the BRCA1 and BRCA2 Breast Cancer–Predisposition Genes

Easton, D. F., Deffenbaugh, A. M., Pruss, D., Frye, C., Wenstrup, R. J., Allen-Brady, K., Tavtigian, S. V., Monteiro, A. N. A., Iversen, E. S., Couch, F. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/521032 · Cited by 455

Increased exonic de novo mutation rate in individuals with schizophrenia

Girard, S. L., Gauthier, J., Noreau, A., Xiong, L., Zhou, S., Jouan, L., Dionne-Laporte, A., Spiegelman, D., Henrion, E., Diallo, O., et al. (2011) · Nature Genetics · doi:10.1038/ng.886 · Cited by 438

Hypomorphic mutations in PRF1, MUNC13-4, and STXBP2 are associated with adult-onset familial HLH

Zhang, K., Jordan, M. B., Marsh, R. A., Johnson, J. A., Kissell, D., Meller, J., Villanueva, J., Risma, K. A., Wei, Q., Klein, P. S., et al. (2011) · Blood · doi:10.1182/blood-2011-07-370148 · Cited by 428

High-risk Melanoma Susceptibility Genes and Pancreatic Cancer, Neural System Tumors, and Uveal Melanoma across GenoMEL

Goldstein, A. M., Chan, M., Harland, M., Gillanders, E. M., Hayward, N. K., Avril, M.-F., Azizi, E., Bianchi-Scarra, G., Bishop, D. T., Bressac-de Paillerets, B., et al. (2006) · Cancer Research · doi:10.1158/0008-5472.can-06-0494 · Cited by 426

Regional missense constraint improves variant deleteriousness prediction

Samocha, K. E., Kosmicki, J. A., Karczewski, K. J., O’Donnell-Luria, A. H., Pierce-Hoffman, E., MacArthur, D. G., Neale, B. M., & Daly, M. J. (2017) · doi:10.1101/148353 · Cited by 351

A quantitative measure of error minimization in the genetic code

Haig, D., & Hurst, L. D. (1991) · Journal of Molecular Evolution · doi:10.1007/bf02103132 · Cited by 337

Genes and the parsing of cognitive processes

Goldberg, T. E., & Weinberger, D. R. (2004) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2004.05.011 · Cited by 356

Genetic load: genomic estimates and applications in non-model animals

Bertorelle, G., Raffini, F., Bosse, M., Bortoluzzi, C., Iannucci, A., Trucchi, E., Morales, H. E., & van Oosterhout, C. (2022) · Nature Reviews Genetics · doi:10.1038/s41576-022-00448-x · Cited by 306

Patterns of coding variation in the complete exomes of three Neandertals

Castellano, S., Parra, G., Sánchez-Quinto, F. A., Racimo, F., Kuhlwilm, M., Kircher, M., Sawyer, S., Fu, Q., Heinze, A., Nickel, B., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405138111 · Cited by 247

TCR contact residue hydrophobicity is a hallmark of immunogenic CD8 + T cell epitopes

Chowell, D., Krishna, S., Becker, P. D., Cocita, C., Shu, J., Tan, X., Greenberg, P. D., Klavinskis, L. S., Blattman, J. N., & Anderson, K. S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1500973112 · Cited by 239

Mutations in the GABA Transporter SLC6A1 Cause Epilepsy with Myoclonic-Atonic Seizures

Carvill, G. L., McMahon, J. M., Schneider, A., Zemel, M., Myers, C. T., Saykally, J., Nguyen, J., Robbiano, A., Zara, F., Specchio, N., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.02.016 · Cited by 227

In silico analysis of missense substitutions using sequence-alignment based methods

Tavtigian, S. V., Greenblatt, M. S., Lesueur, F., Byrnes, G. B., & for the IARC Unclassified Genetic Variants Working Group (2008) · Human Mutation · doi:10.1002/humu.20892 · Cited by 199

Point Mutations (Thr240Arg and Ala311Stop) in theParkinGene

Hattori, N., Matsumine, H., Asakawa, S., Kitada, T., Yoshino, H., Elibol, B., Brookes, A. J., Yamamura, Y., Kobayashi, T., Wang, M., et al. (1998) · Biochemical and Biophysical Research Communications · doi:10.1006/bbrc.1998.9134 · Cited by 181

On Reduced Amino Acid Alphabets for Phylogenetic Inference

Susko, E., & Roger, A. J. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm144 · Cited by 177

CoV-GLUE: A Web Application for Tracking SARS-CoV-2 Genomic Variation

Singer, J., Gifford, R., Cotten, M., & Robertson, D. (2020) · doi:10.20944/preprints202006.0225.v1 · Cited by 167

Predicting functional effects of missense variants in voltage-gated sodium and calcium channels

Heyne, H. O., Baez-Nieto, D., Iqbal, S., Palmer, D. S., Brunklaus, A., May, P., Collaborative, E., Johannesen, K. M., Lauxmann, S., Lemke, J. R., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay6848 · Cited by 140

The origin and evolution of Ebola and Marburg viruses

Suzuki, Y., & Gojobori, T. (1997) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a025820 · Cited by 108

A catalog of single nucleotide changes distinguishing modern humans from archaic hominins

Kuhlwilm, M., & Boeckx, C. (2019) · Scientific Reports · doi:10.1038/s41598-019-44877-x · Cited by 108

Deep genome sequencing and variation analysis of 13 inbred mouse strains defines candidate phenotypic alleles, private variation and homozygous truncating mutations

Doran, A. G., Wong, K., Flint, J., Adams, D. J., Hunter, K. W., & Keane, T. M. (2016) · Genome Biology · doi:10.1186/s13059-016-1024-y · Cited by 101

Distribution of the strength of selection against amino acid replacements in human proteins.

Yampolsky, L. Y., Kondrashov, F. A., & Kondrashov, A. S. (2005) · Human Molecular Genetics · doi:10.1093/hmg/ddi350 · Cited by 95

The mitochondrial‐derived peptide MOTS ‐c: a player in exceptional longevity?

Fuku, N., Pareja‐Galeano, H., Zempo, H., Alis, R., Arai, Y., Lucia, A., & Hirose, N. (2015) · Aging Cell · doi:10.1111/acel.12389 · Cited by 98

Genotype phenotype associations across the voltage-gated sodium channel family

Brunklaus, A., Ellis, R., Reavey, E., Semsarian, C., & Zuberi, S. M. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2014-102608 · Cited by 92

Two Novel Mutations at Exon 8 of the Sequestosome 1 (SQSTM1) Gene in an Italian Series of Patients Affected by Paget's Disease of Bone (PDB)

Falchetti, A., Di Stefano, M., Marini, F., Del Monte, F., Mavilia, C., Strigoli, D., De Feo, M. L., Isaia, G., Masi, L., Amedei, A., et al. (2004) · Journal of Bone and Mineral Research · doi:10.1359/jbmr.040203 · Cited by 87

High-Resolution Homozygosity Mapping Is a Powerful Tool to Detect Novel Mutations Causative of Autosomal Recessive RP in the Dutch Population

Collin, R. W. J., van den Born, L. I., Klevering, B. J., de Castro-Miró, M., Littink, K. W., Arimadyo, K., Azam, M., Yazar, V., Zonneveld, M. N., Paun, C. C., et al. (2011) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.10-6185 · Cited by 79

A Neutral Origin for Error Minimization in the Genetic Code

Massey, S. E. (2008) · Journal of Molecular Evolution · doi:10.1007/s00239-008-9167-4 · Cited by 75

A new criterion and method for amino acid classification

Kosiol, C., Goldman, N., & H. Buttimore, N. (2004) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2003.12.010 · Cited by 70

Evolutionary pattern in the OXT-OXTR system in primates: Coevolution and positive selection footprints

Vargas-Pinilla, P., Paixão-Côrtes, V. R., Paré, P., Tovo-Rodrigues, L., Vieira, C. M. D. A. G., Xavier, A., Comas, D., Pissinatti, A., Sinigaglia, M., Rigo, M. M., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1419399112 · Cited by 59

The neutral emergence of error minimized genetic codes superior to the standard genetic code

Massey, S. E. (2016) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2016.08.022 · Cited by 48

Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of a diverse feature set

Stein, D., Kars, M. E., Wu, Y., Bayrak, Ç. S., Stenson, P. D., Cooper, D. N., Schlessinger, A., & Itan, Y. (2023) · Genome Medicine · doi:10.1186/s13073-023-01261-9 · Cited by 53

Genetic variation in telomeric repeat binding factors 1 and 2 in aplastic anemia

Savage, S. A., Calado, R. T., Xin, Z.-T., Ly, H., Young, N. S., & Chanock, S. J. (2006) · Experimental Hematology · doi:10.1016/j.exphem.2006.02.008 · Cited by 47

Genetic Code Evolution Reveals the Neutral Emergence of Mutational Robustness, and Information as an Evolutionary Constraint

Massey, S. (2015) · Life · doi:10.3390/life5021301 · Cited by 38

Correspondence between functional scores from deep mutational scans and predicted effects on protein stability

Gerasimavicius, L., Livesey, B. J., & Marsh, J. A. (2023) · Protein Science · doi:10.1002/pro.4688 · Cited by 41

Identification of a region required for TSC1 stability by functional analysis of TSC1missense mutations found in individuals with tuberous sclerosis complex

Mozaffari, M., Hoogeveen-Westerveld, M., Kwiatkowski, D., Sampson, J., Ekong, R., Povey, S., den Dunnen, J. T., van den Ouweland, A., Halley, D., & Nellist, M. (2009) · BMC Medical Genetics · doi:10.1186/1471-2350-10-88 · Cited by 36

Further defining the phenotypic spectrum of B4GALT7 mutations

Salter, C. G., Davies, J. H., Moon, R. J., Fairhurst, J., Bunyan, D., Study, D., & Foulds, N. (2016) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.37604 · Cited by 36

Bridging machine learning and peptide design for cancer treatment: a comprehensive review

Rezaee, K., & Eslami, H. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11148-3 · Cited by 34

Genomic signatures of domestication on neurogenetic genes in Drosophila melanogaster

Stanley, C. E., & Kulathinal, R. J. (2016) · BMC Evolutionary Biology · doi:10.1186/s12862-015-0580-1 · Cited by 29

TRPA1 rare variants in chronic neuropathic and nociplastic pain patients

Marchi, M., Salvi, E., Andelic, M., Mehmeti, E., D'Amato, I., Cazzato, D., Chiappori, F., Lombardi, R., Cartelli, D., Devigili, G., et al. (2023) · Pain · doi:10.1097/j.pain.0000000000002905 · Cited by 29

Two Polymorphic Variants of ABCC1 Selectively Alter Drug Resistance and Inhibitor Sensitivity of the Multidrug and Organic Anion Transporter Multidrug Resistance Protein 1

Conseil, G., & Cole, S. P. C. (2013) · Drug Metabolism and Disposition · doi:10.1124/dmd.113.054213 · Cited by 28

WWOX developmental and epileptic encephalopathy: Understanding the epileptology and the mortality risk

Oliver, K. L., Trivisano, M., Mandelstam, S. A., De Dominicis, A., Francis, D. I., Green, T. E., Muir, A. M., Chowdhary, A., Hertzberg, C., Goldhahn, K., et al. (2023) · Epilepsia · doi:10.1111/epi.17542 · Cited by 23

Biallelic hypomorphic variants in ALDH1A2 cause a novel lethal human multiple congenital anomaly syndrome encompassing diaphragmatic, pulmonary, and cardiovascular defects

Beecroft, S. J., Ayala, M., McGillivray, G., Nanda, V., Agolini, E., Novelli, A., Digilio, M. C., Dotta, A., Carrozzo, R., Clayton, J., et al. (2021) · Human Mutation · doi:10.1002/humu.24179 · Cited by 25

A comprehensive WGS-based pipeline for the identification of new candidate genes in inherited retinal dystrophies

González-del Pozo, M., Fernández-Suárez, E., Bravo-Gil, N., Méndez-Vidal, C., Martín-Sánchez, M., Rodríguez-de la Rúa, E., Ramos-Jiménez, M., Morillo-Sánchez, M. J., Borrego, S., & Antiñolo, G. (2022) · npj Genomic Medicine · doi:10.1038/s41525-022-00286-0 · Cited by 21

The identification and functional implications of human-specific “fixed” amino acid substitutions in the glutamate receptor family

Goto, H., Watanabe, K., Araragi, N., Kageyama, R., Tanaka, K., Kuroki, Y., Toyoda, A., Hattori, M., Sakaki, Y., Fujiyama, A., et al. (2009) · BMC Evolutionary Biology · doi:10.1186/1471-2148-9-224 · Cited by 16

The case for an error minimizing set of coding amino acids

Torabi, N., Goodarzi, H., & Shateri Najafabadi, H. (2007) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2006.09.021 · Cited by 13

Clinical and Genetic Characterization of Craniosynostosis in Saudi Arabia

Alghamdi, M., Alhumsi, T. R., Altweijri, I., Alkhamis, W. H., Barasain, O., Cardona-Londoño, K. J., Ramakrishnan, R., Guzmán-Vega, F. J., Arold, S. T., Ali, G., et al. (2021) · Frontiers in Pediatrics · doi:10.3389/fped.2021.582816 · Cited by 15

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning

Feng, M., Wei, X., Zheng, X., Liu, L., Lin, L., Xia, M., He, G., Shi, Y., & Lu, Q. (2024) · Nature Communications · doi:10.1038/s41467-024-52580-3 · Cited by 15

“But Mouse, You Are Not Alone”: On Some Severe Acute Respiratory Syndrome Coronavirus 2 Variants Infecting Mice

Kuiper, M. J., Wilson, L. O. W., Mangalaganesh, S., Lee, C., Reti, D., & Vasan, S. S. (2021) · ILAR Journal · doi:10.1093/ilar/ilab031 · Cited by 14

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Crandall, J. G., Zhou, X., Rokas, A., & Hittinger, C. T. (2024) · Molecular Biology and Evolution · doi:10.1093/molbev/msae228 · Cited by 7

Decomposing information into copying versus transformation

Kolchinsky, A., & Corominas-Murtra, B. (2020) · Journal of The Royal Society Interface · doi:10.1098/rsif.2019.0623 · Cited by 5

StackDPP: a stacking ensemble based DNA-binding protein prediction model

Ahmed, S. H., Bose, D. B., Khandoker, R., & Rahman, M. S. (2024) · BMC Bioinformatics · doi:10.1186/s12859-024-05714-9 · Cited by 5

Correspondence between functional scores from deep mutational scans and predicted effects on protein stability

Gerasimavicius, L., Livesey, B. J., & Marsh, J. A. (2023) · doi:10.1101/2023.02.03.527007 · Cited by 5

Forecasting protein evolution by integrating birth-death population models with structurally constrained substitution models

Ferreiro, D., González-Vázquez, L. D., Prado-Comesaña, A., & Arenas, M. (2025) · eLife · doi:10.7554/elife.106365.3 · Cited by 3

Lineage-specific amino acids define functional attributes of the protomer-protomer interfaces for the Rad51 and Dmc1 recombinases

Petassi, M., Shin, Y., Jessop, A. M., Morse, K., Kim, S. Y., Kuppa, S., Matei, R., Raina, V. B., & Greene, E. C. (2026) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2025.111019 · Cited by 2

Much ado about nothing: modeling amino acid replacement with predicted protein structures

(2026) · doi:10.1093/bioinformatics/btag188 · Cited by 1

ASCARIS: Positional feature annotation and protein structure-based representation of single amino acid variations

Cankara, F., & Doğan, T. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.09.017 · Cited by 1

Molecular Origins of the Mendelian Rare Diseases Reviewed by Orpha.net: A Structural Bioinformatics Investigation

Visibelli, A., Finetti, R., Niccolai, N., Spiga, O., & Santucci, A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25136953 · Cited by 1

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning

Feng, M., Wei, X., Zheng, X., Liu, L., Lin, L., Xia, M., He, G., Shi, Y., & Lu, Q. (2024) · doi:10.1101/2024.04.01.587546