Sequence-Based Prediction of RNA-Binding Residues in Proteins

  • Rasna R. Walia
  • Yasser EL-Manzalawy
  • Vasant G. Honavar
  • Drena Dobbs
Part of the Methods in Molecular Biology book series (MIMB, volume 1484)


Identifying individual residues in the interfaces of protein–RNA complexes is important for understanding the molecular determinants of protein–RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein–RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein–RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

Key words

Protein–RNA interfaces Binding site prediction Machine learning RNA-binding proteins (RBPs) Ribonucleoprotein particles (RNPs) Homology-based prediction RNABindRPlus SNBRFinder PS-PRIP FastRNABindR 



This work was supported in part by NSF DBI0923827 to DD, by NIH GM066387 to VGH and DD, by a Presidential Initiative for Interdisciplinary Research (PIIR) award to DD from Iowa State University, and by the Edward Frymoyer Chair in Information Sciences and Technology held by VGH at Pennsylvania State University. RRW is currently supported by an appointment to the ARS-USDA Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the US Department of Energy (DOE) and USDA. ORISE is managed by ORAU under DOE contract number DE-AC05-06OR23100. We thank Carla Mann and Usha Muppirala for valuable discussions.


  1. 1.
    Re A, Joshi T, Kulberkyte E et al (2014) RNA-protein interactions: an overview. Methods Mol Biol 1097:491–521CrossRefPubMedGoogle Scholar
  2. 2.
    Lee Y, Rio DC (2015) Mechanisms and regulation of alternative pre-mRNA splicing. Annu Rev Biochem 84:291–323CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Fu X-D, Ares M Jr (2014) Context-dependent control of alternative splicing by RNA-binding proteins. Nat Rev Genet 15(10):689–701CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Singh G, Pratt G, Yeo GW et al (2015) The clothes make the mRNA: past and present trends in mRNP fashion. Annu Rev Biochem 84:325–354CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Bryant CD, Yazdani N (2016) RNA binding proteins, neural development and the addictions. Genes Brain Behav 15(1):169–186.Google Scholar
  6. 6.
    Hogg JR, Collins K (2008) Structured non-coding RNAs and the RNP renaissance. Curr Opin Chem Biol 12(6):684–689CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Cech TR, Steitz JA (2014) The noncoding RNA revolution-trashing old rules to forge new ones. Cell 157(1):77–94CrossRefPubMedGoogle Scholar
  8. 8.
    Castello A, Hentze MW, Preiss T (2015) Metabolic enzymes enjoying new partnerships as RNA-binding proteins. Trends Endocrinol Metab 26(12):746–757CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Beckmann BM, Horos R, Fischer B et al (2015) The RNA-binding proteomes from yeast to man harbour conserved enigmRBPs. Nat Commun 6:10127CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Lin Y, Protter DS, Rosen MK et al (2015) Formation and maturation of phase-separated liquid droplets by RNA-binding proteins. Mol Cell 60(2):208–219CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Kafasla P, Skliris A, Kontoyiannis DL (2014) Post-transcriptional coordination of immunological responses by RNA-binding proteins. Nat Immunol 15(6):492–502CrossRefPubMedGoogle Scholar
  12. 12.
    Darnell RB (2010) RNA regulation in neurologic disease and cancer. Cancer Res Treat 42(3):125–129CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Wurth L, Gebauer F (2015) RNA-binding proteins, multifaceted translational regulators in cancer. Biochim Biophys Acta 1849(7):881–886CrossRefPubMedGoogle Scholar
  14. 14.
    Pilaz LJ, Silver DL (2015) Post-transcriptional regulation in corticogenesis: how RNA-binding proteins help build the brain. Wiley Interdiscip Rev RNA 6(5):501–515CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Gerstberger S, Hafner M, Tuschl T (2014) A census of human RNA-binding proteins. Nat Rev Genet 15(12):829–845CrossRefPubMedGoogle Scholar
  16. 16.
    Neelamraju Y, Hashemikhabir S, Janga SC (2015) The human RBPome: from genes and proteins to human disease. J Proteomics 127(Pt A):61–70CrossRefPubMedGoogle Scholar
  17. 17.
    Vaquerizas JM, Kummerfeld SK, Teichmann SA et al (2009) A census of human transcription factors: function, expression and evolution. Nat Rev Genet 10(4):252–263CrossRefPubMedGoogle Scholar
  18. 18.
    Tsvetanova NG, Klass DM, Salzman J et al (2010) Proteome-wide search reveals unexpected RNA-binding proteins in Saccharomyces cerevisiae. PLoS One 5(9)Google Scholar
  19. 19.
    Castello A, Fischer B, Eichelbaum K et al (2012) Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149(6):1393–1406CrossRefPubMedGoogle Scholar
  20. 20.
    Hashemikhabir S, Neelamraju Y, Janga SC (2015) Database of RNA binding protein expression and disease dynamics (READ DB). Database (Oxford) 2015:bav072Google Scholar
  21. 21.
    Tamburino AM, Ryder SP, Walhout AJ (2013) A compendium of Caenorhabditis elegans RNA binding proteins predicts extensive regulation at multiple levels. G3 (Bethesda) 3(2):297–304CrossRefGoogle Scholar
  22. 22.
    Ray D, Kazan H, Cook KB et al (2013) A compendium of RNA-binding motifs for decoding gene regulation. Nature 499(7457):172–177CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Jiang J, Chan H, Cash DD et al (2015) Structure of Tetrahymena telomerase reveals previously unknown subunits, functions, and interactions. Science 350(6260):aab4070. doi:  10.1126/science.aab4070
  24. 24.
    Zhang X, Ding K, Yu X et al (2015) In situ structures of the segmented genome and RNA polymerase complex inside a dsRNA virus. Nature 527(7579):531–534CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Chen Y, Varani G (2013) Engineering RNA-binding proteins for biology. FEBS J 280(16):3734–3754CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Wei H, Wang Z (2015) Engineering RNA-binding proteins with diverse activities. Wiley Interdiscip Rev RNA 6(6):597–613CrossRefPubMedGoogle Scholar
  27. 27.
    Lunde BM, Moore C, Varani G (2007) RNA-binding proteins: modular design for efficient function. Nat Rev Mol Cell Biol 8(6):479–490CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Varadi M, Zsolyomi F, Guharoy M et al (2015) Functional advantages of conserved intrinsic disorder in RNA-binding proteins. PLoS One 10(10):e0139731CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Calabretta S, Richard S (2015) Emerging roles of disordered sequences in RNA-binding proteins. Trends Biochem Sci 40(11):662–672CrossRefPubMedGoogle Scholar
  30. 30.
    Terribilini M, Lee JH, Yan C et al (2006) Prediction of RNA binding sites in proteins from amino acid sequence. RNA 12(8):1450–1462CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Puton T, Kozlowski L, Tuszynska I et al (2012) Computational methods for prediction of protein-RNA interactions. J Struct Biol 179(3):261–268CrossRefPubMedGoogle Scholar
  32. 32.
    Ke A, Doudna JA (2004) Crystallization of RNA and RNA-protein complexes. Methods 34(3):408–414CrossRefPubMedGoogle Scholar
  33. 33.
    Wu H, Finger LD, Feigon J (2005) Structure determination of protein/RNA complexes by NMR. Methods Enzymol 394:525–545CrossRefPubMedGoogle Scholar
  34. 34.
    Carlomagno T (2014) Present and future of NMR for RNA-protein complexes: a perspective of integrated structural biology. J Magn Reson 241:126–136CrossRefPubMedGoogle Scholar
  35. 35.
    Binshtein E, Ohi MD (2015) Cryo-electron microscopy and the amazing race to atomic resolution. Biochemistry 54(20):3133–3141CrossRefPubMedGoogle Scholar
  36. 36.
    Hennig J, Sattler M (2015) Deciphering the protein-RNA recognition code: combining large-scale quantitative methods with structural biology. Bioessays 37(8):899–908CrossRefPubMedGoogle Scholar
  37. 37.
    Faoro C, Ataide SF (2014) Ribonomic approaches to study the RNA-binding proteome. FEBS Lett 588(20):3649–3664CrossRefPubMedGoogle Scholar
  38. 38.
    McHugh CA, Russell P, Guttman M (2014) Methods for comprehensive experimental identification of RNA-protein interactions. Genome Biol 15(1):203CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Campbell ZT, Wickens M (2015) Probing RNA-protein networks: biochemistry meets genomics. Trends Biochem Sci 40(3):157–164CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Cook KB, Hughes TR, Morris QD (2015) High-throughput characterization of protein-RNA interactions. Brief Funct Genomics 14(1):74–89CrossRefPubMedGoogle Scholar
  41. 41.
    Cook KB, Kazan H, Zuberi K et al (2011) RBPDB: a database of RNA-binding specificities. Nucleic Acids Res 39(Database issue):D301–D308CrossRefPubMedGoogle Scholar
  42. 42.
    Li X, Kazan H, Lipshitz HD et al (2014) Finding the target sites of RNA-binding proteins. Wiley Interdiscip Rev RNA 5(1):111–130CrossRefPubMedGoogle Scholar
  43. 43.
    Kazan H, Morris Q (2013) RBPmotif: a web server for the discovery of sequence and structure preferences of RNA-binding proteins. Nucleic Acids Res 41(Web Server issue):W180–W186CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Banerjee H, Singh R (2008) A simple crosslinking method, CLAMP, to map the sites of RNA-contacting domains within a protein. Methods Mol Biol 488:181–190CrossRefPubMedGoogle Scholar
  45. 45.
    Kramer K, Sachsenberg T, Beckmann BM et al (2014) Photo-cross-linking and high-resolution mass spectrometry for assignment of RNA-binding sites in RNA-binding proteins. Nat Methods 11(10):1064–1070CrossRefPubMedGoogle Scholar
  46. 46.
    Qamar S, Kramer K, Urlaub H (2015) Studying RNA-protein interactions of pre-mRNA complexes by mass spectrometry. Methods Enzymol 558:417–463CrossRefPubMedGoogle Scholar
  47. 47.
    Walia RR, Caragea C, Lewis BA et al (2012) Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. BMC Bioinformatics 13(1):89CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Zhao H, Yang Y, Zhou Y (2013) Prediction of RNA binding proteins comes of age from low resolution to high resolution. Mol Biosyst 9(10):2417–2425CrossRefPubMedGoogle Scholar
  49. 49.
    Nagarajan R, Gromiha MM (2014) Prediction of RNA binding residues: an extensive analysis based on structure and function to select the best predictor. PLoS One 9(3):e91140CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Si J, Cui J, Cheng J et al (2015) Computational prediction of RNA-binding proteins and binding sites. Int J Mol Sci 16(11):26303–26317CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Mitchell A, Chang HY, Daugherty L et al (2015) The InterPro protein families database: the classification resource after 15 years. Nucleic Acids Res 43(Database issue):D213–D221CrossRefPubMedGoogle Scholar
  52. 52.
    Muppirala UK, Lewis BA, Mann CM et al (2016) A motif-based method for predicting interfacial residues in both the RNA and protein components of protein-RNA complexes. Pac Symp Biocomput 2016:445–455. doi: 10.1142/9789814749411_0041 Google Scholar
  53. 53.
    Williamson JR (2000) Induced fit in RNA-protein recognition. Nat Struct Biol 7(10):834–837CrossRefPubMedGoogle Scholar
  54. 54.
    Ellis JJ, Jones S (2008) Evaluating conformational changes in protein structures binding RNA. Proteins 70(4):1518–1526CrossRefPubMedGoogle Scholar
  55. 55.
    Sankar K, Walia R, Mann C et al (2014) An analysis of conformational changes upon RNA-protein binding. In: ACM BCB 2014 5th ACM conference on bioinformatics, computational biology, and health informatics, Washington, DC, 2013. ACM New York, NY, USA ©2014 pp 592–593 doi:  10.1145/2649387.2660790
  56. 56.
    Spriggs RV, Jones S (2009) RNA-binding residues in sequence space: conservation and interaction patterns. Comput Biol Chem 33(5):397–403CrossRefPubMedGoogle Scholar
  57. 57.
    Walia RR, Xue LC, Wilkins K et al (2014) RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins. PLoS One 9(5):e97725CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Yang X, Wang J, Sun J et al (2015) SNBRFinder: a sequence-based hybrid algorithm for enhanced prediction of nucleic acid-binding residues. PLoS One 10(7):e0133260CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Tuszynska I, Matelska D, Magnus M et al (2014) Computational modeling of protein-RNA complex structures. Methods 65(3):310–319CrossRefPubMedGoogle Scholar
  60. 60.
    Gupta A, Gribskov M (2011) The role of RNA sequence and structure in RNA—protein interactions. J Mol Biol 409(4):574–587CrossRefPubMedGoogle Scholar
  61. 61.
    Panwar B, Raghava GP (2015) Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides. Genomics 105(4):197–203CrossRefPubMedGoogle Scholar
  62. 62.
    Mann C, Muppirala UK, Dobbs DL (2016) Computational prediction of RNA-protein interactions. Methods Mol Biol. In pressGoogle Scholar
  63. 63.
    Muppirala UK, Lewis BA, Dobbs D (2013) Computational tools for investigating RNA-protein interaction partners. J Comput Sci Syst Biol 6:182–187Google Scholar
  64. 64.
    Cirillo D, Livi CM, Agostini F et al (2014) Discovery of protein-RNA networks. Mol Biosyst 10(7):1632–1642CrossRefPubMedGoogle Scholar
  65. 65.
    Marchese D, Livi CM, Tartaglia GG (2016) A computational approach for the discovery of protein-RNA networks. Methods Mol Biol 1358:29–39CrossRefPubMedGoogle Scholar
  66. 66.
    Zhao H, Yang Y, Janga SC et al (2014) Prediction and validation of the unexplored RNA-binding protein atlas of the human proteome. Proteins 82(4):640–647CrossRefPubMedGoogle Scholar
  67. 67.
    Kumar M, Gromiha MM, Raghava GP (2011) SVM based prediction of RNA-binding proteins using binding residues and evolutionary information. J Mol Recognit 24(2):303–313CrossRefPubMedGoogle Scholar
  68. 68.
    Berman HM, Westbrook J, Feng Z et al (2000) The protein data bank. Nucleic Acids Res 28(1):235–242CrossRefPubMedPubMedCentralGoogle Scholar
  69. 69.
    Coimbatore Narayanan B, Westbrook J, Ghosh S et al (2014) The nucleic acid database: new features and capabilities. Nucleic Acids Res 42(Database issue):D114–D122CrossRefPubMedGoogle Scholar
  70. 70.
    de Beer TA, Berka K, Thornton JM et al (2014) PDBsum additions. Nucleic Acids Res 42(Database issue):D292–D296CrossRefPubMedGoogle Scholar
  71. 71.
    Laskowski RA, Hutchinson EG, Michie AD et al (1997) PDBsum: a Web-based database of summaries and analyses of all PDB structures. Trends Biochem Sci 22(12):488–490CrossRefPubMedGoogle Scholar
  72. 72.
    Lee S, Blundell TL (2009) BIPA: a database for protein-nucleic acid interaction in 3D structures. Bioinformatics 25(12):1559–1560CrossRefPubMedGoogle Scholar
  73. 73.
    Jones P, Binns D, Chang HY et al (2014) InterProScan 5: genome-scale protein function classification. Bioinformatics 30(9):1236–1240CrossRefPubMedPubMedCentralGoogle Scholar
  74. 74.
    Kirsanov DD, Zanegina ON, Aksianov EA et al (2013) NPIDB: nucleic acid—protein interaction database. Nucleic Acids Res 41(D1):D517–D523CrossRefPubMedGoogle Scholar
  75. 75.
    Park B, Kim H, Han K (2014) DBBP: database of binding pairs in protein-nucleic acid interactions. BMC Bioinformatics 15(Suppl 15):S5CrossRefPubMedPubMedCentralGoogle Scholar
  76. 76.
    Lewis BA, Walia RR, Terribilini M et al (2011) PRIDB: a protein-RNA interface database. Nucleic Acids Res 39(Database issue):D277–D282CrossRefPubMedGoogle Scholar
  77. 77.
    Shulman-Peleg A, Nussinov R, Wolfson HJ (2009) RsiteDB: a database of protein binding pockets that interact with RNA nucleotide bases. Nucleic Acids Res 37(Suppl 1):D369–D373CrossRefPubMedGoogle Scholar
  78. 78.
    Kumar MDS, Bava KA, Gromiha MM et al (2006) ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions. Nucleic Acids Res 34(Database issue):D204–D206CrossRefPubMedGoogle Scholar
  79. 79.
    Vanegas PL, Hudson GA, Davis AR et al (2012) RNA CoSSMos: characterization of secondary structure motifs—a searchable database of secondary structure motifs in RNA three-dimensional structures. Nucleic Acids Res 40(Database issue):D439–D444CrossRefPubMedGoogle Scholar
  80. 80.
    Petrov AI, Zirbel CL, Leontis NB (2013) Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas. RNA 19(10):1327–1340CrossRefPubMedPubMedCentralGoogle Scholar
  81. 81.
    Chojnowski G, Walen T, Bujnicki JM (2014) RNA Bricks—a database of RNA 3D motifs and their interactions. Nucleic Acids Res 42(Database issue):D123–D131CrossRefPubMedGoogle Scholar
  82. 82.
    Livi CM, Klus P, Delli Ponti R et al (2015) catRAPID signature: identification of ribonucleoproteins and RNA-binding regions. Bioinformatics. Oct 31. pii: btv629. [Epub ahead of print]Google Scholar
  83. 83.
    Wang L, Brown SJ (2006) BindN: a web-based tool for efficient prediction of DNA and RNA binding sites in amino acid sequences. Nucleic Acids Res 34(suppl 2):W243–W248CrossRefPubMedPubMedCentralGoogle Scholar
  84. 84.
    Wang L, Huang C, Yang MQ et al (2010) BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features. BMC Syst Biol 4(Suppl 1):S3CrossRefPubMedPubMedCentralGoogle Scholar
  85. 85.
    Zhao H, Yang Y, Zhou Y (2011) Structure-based prediction of RNA-binding domains and RNA-binding sites and application to structural genomics targets. Nucleic Acids Res 39(8):3017–3025CrossRefPubMedGoogle Scholar
  86. 86.
    Kim OTP, Yura K, Go N (2006) Amino acid residue doublet propensity in the protein–RNA interface and its application to RNA interface prediction. Nucleic Acids Res 34(22):6450–6460CrossRefPubMedPubMedCentralGoogle Scholar
  87. 87.
    Carson MB, Langlois R, Lu H (2010) NAPS: a residue-level nucleic acid-binding prediction server. Nucleic Acids Res 38(Web Server Issue):W431–W435CrossRefPubMedPubMedCentralGoogle Scholar
  88. 88.
    Pérez-Cano L, Fernández-Recio J (2010) Optimal protein-RNA area, OPRA: a propensity-based method to identify RNA-binding sites on proteins. Proteins 78(1):25–35CrossRefPubMedGoogle Scholar
  89. 89.
    Kumar M, Gromiha MM, Raghava GPS (2008) Prediction of RNA binding sites in a protein using SVM and PSSM profile. Proteins 71(1):189–194CrossRefPubMedGoogle Scholar
  90. 90.
    Ma X, Guo J, Wu J et al (2011) Prediction of RNA-binding residues in proteins from primary sequence using an enriched random forest model with a novel hybrid feature. Proteins 79(4):1230–1239CrossRefPubMedGoogle Scholar
  91. 91.
    Maetschke SR, Yuan Z (2009) Exploiting structural and topological information to improve prediction of RNA-protein binding sites. BMC Bioinformatics 10(1):341CrossRefPubMedPubMedCentralGoogle Scholar
  92. 92.
    Miao Z, Westhof E (2015) Prediction of nucleic acid binding probability in proteins: a neighboring residue network based score. Nucleic Acids Res 43(11):5340–5351CrossRefPubMedPubMedCentralGoogle Scholar
  93. 93.
    Tong J, Jiang P, Lu Z-H (2008) RISP: a web-based server for prediction of RNA-binding sites in proteins. Comput Methods Programs Biomed 90(2):148–153CrossRefPubMedGoogle Scholar
  94. 94.
    Terribilini M, Sander JD, Lee JH et al (2007) RNABindR: a server for analyzing and predicting RNA-binding sites in proteins. Nucleic Acids Res 35(Web Server issue):W578–W584CrossRefPubMedPubMedCentralGoogle Scholar
  95. 95.
    Yang Y, Zhao H, Wang J et al (2014) SPOT-Seq-RNA: predicting protein-RNA complex structure and RNA-binding function by fold recognition and binding affinity prediction. Methods Mol Biol 1137:119–130CrossRefPubMedPubMedCentralGoogle Scholar
  96. 96.
    Remmert M, Biegert A, Hauser A et al (2012) HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment. Nat Methods 9(2):173–175CrossRefGoogle Scholar
  97. 97.
    Altschul SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215(3):403–410CrossRefPubMedGoogle Scholar
  98. 98.
    Altschul SF, Madden TL, Schaffer AA et al (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25(17):3389–3402CrossRefPubMedPubMedCentralGoogle Scholar
  99. 99.
    Lambert N, Robertson A, Jangi M et al (2014) RNA Bind-n-Seq: quantitative assessment of the sequence and structural binding specificity of RNA binding proteins. Mol Cell 54(5):887–900CrossRefPubMedPubMedCentralGoogle Scholar
  100. 100.
    Paz I, Kosti I, Ares M Jr et al (2014) RBPmap: a web server for mapping binding sites of RNA-binding proteins. Nucleic Acids Res 42(Web Server issue):W361–W367CrossRefPubMedPubMedCentralGoogle Scholar
  101. 101.
    Jones S, Daley DT, Luscombe NM et al (2001) Protein-RNA interactions: a structural analysis. Nucleic Acids Res 29(4):943–954CrossRefPubMedPubMedCentralGoogle Scholar
  102. 102.
    Stormo GD, Schneider TD, Gold L et al (1982) Use of the “Perceptron” algorithm to distinguish translational initiation sites in E. coli. Nucleic Acids Res 10(9):2997–3011CrossRefPubMedPubMedCentralGoogle Scholar
  103. 103.
    Henry VJ, Bandrowski AE, Pepin AS et al (2014) OMICtools: an informative directory for multi-omic data analysis. Database (Oxford). doi: 10.1093/database/bau069 Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Rasna R. Walia
    • 1
  • Yasser EL-Manzalawy
    • 2
  • Vasant G. Honavar
    • 2
  • Drena Dobbs
    • 3
  1. 1.USDA-ARSAmesUSA
  2. 2.College of Information Sciences and TechnologyPennsylvania State UniversityUniversity ParkUSA
  3. 3.Genetics, Development and Cell Biology DepartmentIowa State UniversityAmesUSA

Personalised recommendations