I. S. Mian
Honorary Professor
Department of Computer Science
University College London
66 Gower Street
London WC1E 6BT

Research interests

Dark Information

Any collection of interacting entities – animate or inanimate, real or virtual, ancient or modern – can be abstracted and analysed as a “black box” communication channel. Deeper understanding is possible if details of the underlying system are available. Information theory, communication theory and network information theory offer a unique palette of ideas, concepts, and techniques for exploring natural systems: from the ecological, evolutionary, and molecular factors contributing to their formation, stability, and function; through how they adapt and respond to environmental stimuli; to potential insights that may assist in sustaining and improving the health of organisms and ecosystems.

Dark Information describes information that is neither easily detected nor understood in isolation, but that nonetheless exists and is open to careful theoretical inspection and amenable to experimental enquiry. In a network of intercommunicating elements, dark information resides in the constituent elements themselves (what is present), in their spatiotemporal contexts (what is present where and when), and in their interactions (what speaks to what).

Resource constrained-communication and resource constrained-computation

In the biosphere, a message is a quantity varying in space or time that might provide information about the status of the physical system that sent it. In the digital world, a signal is a function that conveys information about the attributes or behaviour of a phenomenon. Typically, the information in a message or a signal is accompanied by noise – be it undesirable random disturbances or unwanted messages or signals which conflict with the desired message or signal (for example, cross-talk) – and transmission takes place in the presence of third parties (adversaries, eavesdroppers, internal attackers, and external attackers). To convey useful information, a sender must utilise energy and materials to impose spatial and temporal structure on the message or signal and/or prevent its interception. However, there are limits on the resources available for communication in the physical and virtual realms: energy, materials, space, and time are invariably scarce and at a premium. Thus, resource use is, or needs to be, minimal and minimised in both arenas.




[1]     A.M. Phillips and I.S. Mian. Your Genetic Payday – Genomics Goes Blockchain – An Exploration of Law, Governance, and Societal Impact. 2018. In preparation.

[2]     I.S. Mian and C. Rose. Tokens, waves, fields and physical structure as carriers of information and/or the information itself in biology. 2018. In preparation.

[3]     N. von Huth, M. Chang, I.S. Mian, and P. Stenetorp. Science, technology, engineering, mathematics and medicine research funding in the United Kingdom: how much is allocated to “agroecology”? 2018. In preparation.

[4]     M. Chang, C.-H. Huang, and I.S. Mian. A data science and historical global political ecology perspective on the financial system, agriculture and climate: from the trans-Atlantic slave trade to agroecology. 2018. In preparation.

[5]     M. Chang and I.S. Mian. Big Data, data science, agroecology and agricultural policy: pitfalls and promises. Development, 2018. Under revision.

[6]     A.M. Phillips and I.S. Mian. Governance and Assessment of Future Spaces: a discussion of some issues raised by the possibilities of human-machine mergers. Development, 2018. Under revision.

[7]     I.S. Mian, D. Twiselton, and D. Timm. What is the resource footprint of a computer science department? Place, People, and Pedagogy. Development, 2018. Under revision.

[8]     C. Rose and I.S. Mian. Inscribed Matter Communication: Part I. IEEE Trans Molecular, Biological, and Multi-Scale Communications, 2:209 – 227, 2016. [Online] [PDF].

[9]     C. Rose and I.S. Mian. Inscribed Matter Communication: Part II. IEEE Trans Molecular, Biological, and Multi-Scale Communications, 2:228 – 239, 2016. [Online] [PDF].

[10]     C. Rose and I.S. Mian. A fundamental framework for molecular communication channels: timing & payload. In IEEE Int Conf Communications (ICC). 2015. [Online] [PDF].

[11]     R. Bhat, M. Chakraborty, I.S. Mian, and S.A. Newman. Structural divergence in vertebrate phylogeny of a duplicated prototype galectin. Genome Biol Evol, 6:2721–2730, 2014. [Online; Supplementary Data] [PDF].

[12]     C. Rose and I.S. Mian. Signaling with identical tokens: upper bounds with energy constraints. In IEEE Int Symp Information Theory (ISIT), pages 1817–1821. 2014. [Online] [PDF].

[13]     C. Rose, I.S. Mian, and R. Song. Timing channels with multiple identical quanta. IEEE Trans Information Theory, 2013. To be published. [Online] [PDF].

[14]     C. Rose and I.S. Mian. Signaling with identical tokens: lower bounds with energy constraints. In IEEE Int Symp Information Theory (ISIT), pages 1839–1843, 2013. [Online] [PDF].

[15]     R. Song, C. Rose, Y.-L. Tsai, and I.S. Mian. Wireless signaling with identical quanta. In IEEE Wireless Communications and Networking Conference: PHY and Fundamentals (WCNC), pages 699–703. 2012. [Online] [PDF].

[16]     I.S. Mian and C. Rose. Communication theory and multicellular biology. Integr Biol, 3:350–367, 2011.

[17]     Y.-L. Tsai, C. Rose, R. Song, and I.S. Mian. An additive exponential noise channel with a transmission deadline. In IEEE Int Symp Information Theory (ISIT), pages 598–602, 2011. [Online] [PDF].

[18]     R.J. McFarlane, I.S. Mian, and J.Z. Dalgaard. The many facets of the Tim-Tipin protein families’ roles in chromosome biology. Cell Cycle, 9:700–705, 2010. [Online] [PDF].

[19]     S. Bhadra, C. Bhattacharyya, N.R. Chandra, and I.S. Mian. A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data. Algorithms Mol Biol, 4:5, 2009. [Online] [PDF].

[20]     T. Inagawa, T. Yamada-Inagawa, T. Eydmann, I.S. Mian, T.S. Wang, and J.Z. Dalgaard. Schizosaccharomyces pombe Rtf2 mediates site-specific replication termination by inhibiting replication restart. Proc Natl Acad Sci USA, 106:7927–7932, 2009. [Online] [PDF].

[21]     A. Rizki, V.M. Weaver, S.Y. Lee, G.I. Rozenberg, K. Chin, C.A. Myers, J.L. Bascom, J.D. Mott, J.R. Semeiks, L.R. Grate, I.S. Mian, A.D. Borowsky, R.A. Jensen, M.O. Idowu, F. Chen, D.J. Chen, O.W. Petersen, J.W. Gray, and M.J. Bissell. A human breast cell model of preinvasive to invasive transition. Cancer Res, 68:1378–1387, 2008. [Online] [PDF].

[22]     J.Y. Park, M.-O. Cho, S. Leonard, R.B. Calder, I.S. Mian, W.H. Kim, S. Wijnhoven, H. van Steeg, J. Mitchell, G.T.J. van der Horst, J. Hoeijmakers, P. Cohen, J. Vijg, and Y. Suh. Homeostatic imbalance between apoptosis and cell renewal in the liver of premature aging XpdTTD mice. PLoS ONE, 3:e2346, 2008. [Online] [PDF].

[23]     T. Eydmann, E. Sommariva, T. Inagawa, S. Mian, A.J.S. Klar, and J.Z. Dalgaard. Rtf1-mediated eukaryotic site-specific replication termination. Genetics, 180:27–39, 2008. [Online] [PDF].

[24]     P.C. Abad, J. Lewis, I.S. Mian, D. Knowles, J. Sturgis, S. Badve, J. Xie, and S.A. Lelièvre. NuMA influences higher order chromatin organization in human mammary epithelium. Mol Biol Cell, 18:348–361, 2007. [Online] [PDF].

[25]     R.B. Calder, R.B. Beems, H. van Steeg, I.S. Mian, P.H.M. Lohman, and J. Vijg. MPHASYS: A mouse phenotype analysis system. BMC Bioinformatics, 8:183, 2007. [Online] [PDF].

[26]     D. Chen, Q. Lin, I.S. Mian, J. Reed, and E.E. Medrano. The multiple roles of the oncogenic protein SKI in human malignant melanoma. In V.J. Hearing and S.P.L. Leong, editors, From Melanocytes to Melanoma, pages 211–222. Humana Press, 2006. [Online] [PDF].

[27]     D.M. Blei, K. Franks, M.I. Jordan, and I.S. Mian. Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to aging. BMC Bioinformatics, 7:250, 2006. [Online] [PDF].

[28]     J.R. Semeiks, A. Rizki, M.J. Bissell, and I.S. Mian. Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features. BMC Bioinformatics, 7:147, 2006. [Online] [PDF].

[29]     I.S. Mian, E.A. Worthey, and R. Salavati. Taking U out, with two nucleases? BMC Bioinformatics, 7:305, 2006. [Online] [PDF].

[30]     V. Hegde, M. Wang, I.S. Mian, L. Spyres, and W.A. Deutsch. The high binding affinity of human ribosomal protein S3 to 7,8-dihydro-8-oxoguanine is abrogated by a single amino acid change. DNA Repair, 5:810–815, 2006. [Online] [PDF].

[31]     S. Huang, L. Lee, N.B. Hanson, C. Lenaerts, H. Hoehn, M. Poot, C.D. Rubin, D.F. Chen, C.C. Yang, H. Juch, T. Dorn, R. Spiegel, E.A. Oral, M. Abid, C. Battisti, E. Lucci-Cordisco, G. Neri, E.H. Steed, A. Kidd, W. Isley, D. Showalter, J.L. Vittone, A. Konstantinow, J. Ring, P. Meyer, S.L. Wenger, A. von Herbay, U. Wollina, M. Schuelke, C.R. Huizenga, D.F. Leistritz, G.M. Martin, I.S. Mian, and J. Oshima. The spectrum of WRN mutations in Werner syndrome patients. Hum Mutat, 27:558–567, 2006. [Online] [PDF].

[32]     J.R. Semeiks, L.R. Grate, and I.S. Mian. Text-based analysis of genes, proteins, cancer, and aging. Mech Ageing Dev, 126:193–208, 2005. [Online] [PDF].

[33]     W. Wu, E.P. Xing, I.S. Mian, and M.J. Bissell. Evaluation of normalization methods for cDNA microarray data by classification. BMC Bioinformatics, 6:191, 2005. [Online] [PDF].

[34]     Y. Nakayama, I.S. Mian, T. Kohwi-Shigematsu, and T. Ogawa. A nuclear targeting determinant for SATB1, a genome organizer in the T cell lineage. Cell Cycle, 4:4099–4106, 2005. [Online] [PDF].

[35]     C.K. Patil, I.S. Mian, and J. Campisi. The thorny path linking cellular senescence to organismal aging. Mech Ageing Dev, 126:1040–1045, 2005. [Online] [PDF].

[36]     J.A. Reed, Q. Lin, D. Chen, I.S. Mian, and E.E. Medrano. SKI pathways inducing progression of human melanoma. Cancer Metastasis Rev, 24:265–272, 2005. [Online] [PDF].

[37]     A.V. Loguinov, I.S. Mian, and C.D. Vulpe. Exploratory differential gene expression analysis in microarray experiments with no or limited replication. Genome Biol, 5:R18, 2004. [Online] [PDF].

[38]     C. Bhattacharyya, L.R. Grate, L. El Ghaoui, M.I. Jordan, and I.S. Mian. Robust sparse hyperplane classifiers: application to uncertain molecular profiling data. J Comput Biol, 11:1073–1089, 2004. [Online] [PDF].

[39]     P.C. Abad, I.S. Mian, C. Plachot, A. Nelpurackal, C. Bator-Kelly, and S.A. Lelièvre. The C-terminus of the nuclear protein NuMA: phylogenetic distribution and structure. Protein Sci, 13:2573 – 2577, 2004. [Online] [PDF].

[40]     J.R. Semeiks, L.R. Grate, and I.S. Mian. Networks of genetic loci and the scientific literature. In Fifth Int Conf Complex Systems (ICCS). 2004. [Online or 1, 2] [PDF].

[41]     M.J. Bissell, I.S. Mian, D. Radisky, and E. Turley. Tissue-specificity: Structural cues allow diverse phenotypes from a constant genotype. In S.A. Newman and G.B. Müller, editors, Origination of Organismal Form: Beyond the Gene in Developmental and Evolutionary Biology. Vienna Series in Theoretical Biology. MIT Press, 2003. [Online] [PDF].

[42]     N.F. Lue, Y.-C. Lin, and I.S. Mian. A conserved telomerase motif within the catalytic domain of telomerase reverse transcriptase is specifically required for repeat addition processivity. Mol Cell Biol, 23:8440–8449, 2003. [Online] [PDF].

[43]     L. Chen, L. Lee, B.A. Kudlow, H.G. Dos Santos, O. Sletvold, Y. Shafeghati, E.G. Botha, A. Garg, N.B. Hanson, G.M. Martin, I.S. Mian, B.K. Kennedy, and J. Oshima. LMNA mutations in atypical Werner’s syndrome. Lancet, 362:440–445, 2003. [Online] [PDF].

[44]     D. Bosoy, Y. Peng, I.S. Mian, and N.F. Lue. Conserved N-terminal motifs of telomerase reverse transcriptase required for ribonucleoprotein assembly in vivo. J Biol Chem, 278:3882–3890, 2003. [Online] [PDF].

[45]     C. Bhattacharyya, L.R. Grate, A. Rizki, D.C. Radisky, F.J. Molina, M.I. Jordan, M.J. Bissell, and I.S. Mian. Simultaneous classification and relevant feature identification in high-dimensional spaces: application to molecular profiling data. Signal Processing, 83:729–743, 2003. [Online] [PDF].

[46]     L.R. Grate, C. Bhattacharyya, M.I. Jordan, and I.S. Mian. Integrated analysis of transcript profiling and protein sequence data. Mech Ageing Dev, 124:109–114, 2003. [Online] [PDF].

[47]     M.J. Bissell, A. Rizki, and I.S. Mian. Tissue architecture: the ultimate regulator of breast function. Curr Opin Cell Biol, 15:753–762, 2003. [Online] [PDF].

[48]     E.A. Worthey, A. Schnaufer, I.S. Mian, K. Stuart, and R. Salavati. Comparative analysis of editosome proteins in trypanosomatids. Nucleic Acids Res, 31:6392–6408, 2003. [Online] [PDF].

[49]     S.M. Singh, O. Steinberg-Neifach, I.S. Mian, and N.F. Lue. Analysis of telomerase in Candida albicans: potential role in telomere end protection. Eukaryot Cell, 1:967–977, 2002. [Online] [PDF].

[50]     D.E. Arking, A. Krebsova, M. Macek Jr., M. Macek, A. Arking, I.S. Mian, L. Fried, A. Hamosh, S. Dey, I. McIntosh, and H.C. Dietz. Association of human aging with a functional variant of klotho. Proc Natl Acad Sci USA, 99:856–861, 2002. [Online] [PDF].

[51]     W.R. Holley, I.S. Mian, S.J. Park, B. Rydberg, and A. Chatterjee. A model for interphase chromosomes and evaluation of radiation induced aberrations. Radiat Res, 158:568–580, 2002. [Online] [PDF].

[52]     L.R. Grate, C. Bhattacharyya, M.I. Jordan, and I.S. Mian. Simultaneous relevant feature identification and classification in high-dimensional spaces. In Second International Workshop on Algorithms in Bioinformatics (WABI), pages 1–9. 2002. [Online] [PDF].

[53]     A.M. Earl, M.M. Mohundro, I.S. Mian, and J.R. Battista. The IrrE protein of Deinococcus radiodurans R1 is a novel regulator of recA expression. J Bacteriol, 184:6216–6224, 2002. [Online] [PDF].

[54]     D.N. Everly Jr., P. Feng, I.S. Mian, and G.S. Read. mRNA degradation by the virion host shutoff (VHS) protein of Herpes Simplex virus: genetic and biochemical evidence that VHS is a nuclease. J Virol, 76:8560–8571, 2002. [Online] [PDF].

[55]     J.A. Chekanova, J.A. Dutko, I.S. Mian, and D.A. Belostotsky. Arabadopsis thaliana exosome subunit AtRrp4p is a hydrolytic 3′→ 5 exonuclease containing S1 and KH RNA binding domains. Nucleic Acids Res, 30:695–700, 2002. [Online] [PDF].

[56]     M.L. Chow, E.J. Moler, and I.S. Mian. Identifying marker genes in transcription profile data using a mixture of feature relevance experts. Physiol Genomics, 5:99–111, 2001. [Online] [PDF].

[57]     G.S.C. Dance, P. Beemiller, Y. Yang, D. van Mater, I.S. Mian, and H.F. Smith. Identification of the yeast cytidine deaminase CDD1 as an orphan C to U RNA editase. Nucleic Acids Res, 29:1772–1780, 2001. [Online] [PDF].

[58]     Y. Peng, I.S. Mian, and N.F. Lue. Analysis of telomerase processivity: mechanistic similarity to HIV-1 reverse transcriptase and role in telomere maintenance. Mol Cell, 7:1201–1211, 2001. [Online] [PDF].

[59]     S. Glande, L.A. Dickinson, I.S. Mian, M. Sikorska, and T. Kohwi-Shigematsu. SATB1 cleavage by caspase 6 disrupts PDZ domain-mediated dimerization causing detachment from chromatin early in T-cell apotosis. Mol Cell Biol, 21:5591–5604, 2001. [Online] [PDF].

[60]     V. Hegde, M.R. Kelley, X. Y, I.S. Mian, and W.A. Deutsch. Conversion of the Drosophila S3 bifunctional 8-oxoguanine/β-δ AP DNA repair activities into the human S3 monofunctional β-elimination catalyst through a single amino acid change. J Biol Chem, 276:27591–27596, 2001. [Online] [PDF].

[61]     C.-S. Lim, I.S. Mian, A.F. Dernburg, and J. Campisi. C. elegans clk-2, a gene that limits life span, encodes a telomere length regulator similar to yeast telomere binding protein Tel2p. Curr Biol, 11:1706–1710, 2001. [Online] [PDF].

[62]     H. Bengtsson, B. Calder, I.S. Mian, M. Callow, E. Rubin, and T.P. Speed. Identifying differentially expressed genes in cDNA microarray experiments. Sci Aging Knowledge Environ, 12:8, 2001. [Online] [PDF].

[63]     I.S. Mian and I. Dubchak. Representing and reasoning about protein families using generative and discriminative methods. J Comput Biol, 7:849–862, 2000. [Online] [PDF].

[64]     E.J. Moler, M.L. Chow, and I.S. Mian. Analysis of molecular profile data using generative and discriminative methods. Physiol Genomics, 4:109–126, 2000. [Online] [PDF].

[65]     E.J. Moler, D.C. Radisky, and I.S. Mian. Integrating naïve Bayes models and external knowledge to examine copper and iron homeostasis in Saccharomyces cerevisiae. Physiol Genomics, 4:127–135, 2000. [Online] [PDF].

[66]     J. Xia, Y. Peng, I.S. Mian, and N.F. Lue. Identification of functionally important conserved and non-conserved domains in the N-terminal region of telomerase reverse transcriptase. Mol Cell Biol, 20:5196–5207, 2000. [Online] [PDF].

[67]     H.-M. Chen, K.L. Schmeichel, I.S. Mian, O.W. Petersen, and M.J. Bissell. AZU-1: a candidate breast tumor suppressor with a C-terminal coiled coil domain. Mol Biol Cell, 11:1357–1367, 2000. [Online] [PDF].

[68]     E.A. Gross, G.-R. Li, Z.-Y. Lin, S.E. Ruuska, J.H. Boatright, I.S. Mian, and J.M. Nickerson. Prediction of structural and functional relationships of Repeat 1 of human interphotoreceptor retinoid-binding protein (IRBP) with other proteins. Mol Vis, 6:30–39, 2000. [Online] [PDF].

[69]     E.A. Gross, G.-R. Li, S.E. Ruuska, J.H. Boatright, I.S. Mian, and J.M. Nickerson. Effects of dispersed point substitutions in Repeat 1 of human interphotoreceptor retinoid-binding protein (IRBP). Mol Vis, 6:40–50, 2000. [Online] [PDF].

[70]     K. Murphy and S. Mian. Modelling gene expression data using Dynamic Bayesian Networks. Technical report, Department of Computer Science, University of California Berkeley, 1999. [Online] [PDF].

[71]     I.S. Mian, M.J. Moser, W.R. Holley, and A. Chatterjee. Statistical modelling and phylogenetic analysis of a deaminase domain. J Comput Biol, 5:57–72, 1998. [Online] [PDF].

[72]     I.S. Mian and M.J. Moser. The Fanconi anemia complementation group A protein contains a peroxidase domain. Mol Genet Metab, 63:230–234, 1998. [Online] [PDF].

[73]     I.S. Mian. Sequence, structural, functional and phylogenetic analysis of three glycosidase families. Blood Cells Mol Dis, 24:83–100, 1998. [Online] [PDF; Colour figures: 1, 2, 3, 4, 5, 6].

[74]     S. Huang, B. Li, M.D. Gray, J. Oshima, I.S. Mian, and J. Campisi. The premature ageing syndrome protein, WRN, is a 3′→ 5 exonuclease. Nat Genet, 20:114–116, 1998. [Online] [PDF].

[75]     B. Rydberg, W.R. Holley, I.S. Mian, and A. Chatterjee. Chromatin conformation in living cells: support for a zig-zag model of the 30 nm chromatin fiber. J Mol Biol, 284:71–84, 1998. [Online] [PDF].

[76]     W.R. Holley, A. Chatterjee, I.S. Mian, and B. Rydberg. Theoretical modeling of radiation effects. In R.N. Sharan, editor, Trends in Radiation and Cancer Biology, pages 12–21. Forschungszentrum Jülich GmbH, Jülich, Germany, 1998.

[77]     I.S. Mian. Comparative sequence analysis of ribonucleases HII, III, II, PH and D. Nucleic Acids Res, 25:3187–3195, 1997. [Online] [PDB].

[78]     A. Herbert, J. Alfken, Y.-G. Kim, I.S. Mian, K. Nishikura, and A. Rich. A Z-DNA binding domain present in human editing enzyme, double-stranded RNA adenosine deaminase. Proc Natl Acad Sci USA, 94:8421–8426, 1997. [Online] [PDF].

[79]     J.Z. Dalgaard, M.J. Moser, R. Hughey, and I.S. Mian. Statistical modeling, phylogenetic analysis and structure prediction of a protein splicing domain common to inteins and hedgehog proteins. J Comput Biol, 4:193–214, 1997. [Online] [PDF].

[80]     M.J. Moser, W.R. Holley, A. Chatterjee, and I.S. Mian. The proofreading domain of Escherichia coli DNA polymerase I and other DNA and/or RNA exonuclease domains. Nucleic Acids Res, 25:5110–5118, 1997. [Online] [PDF].

[81]     J.Z. Dalgaard, A. Klar, M.J. Moser, W.R. Holley, A. Chatterjee, and I.S. Mian. Statistical modeling and analysis of the LAGLIDADG family of site-specific endonucleases and identification of an intein that encodes a site-specific endonuclease of the HNH family. Nucleic Acids Res, 25:4626–4638, 1997. [Online] [PDF].

[82]     G.M. Martin and I.S. Mian. Ageing: New mice for old questions. Nature, 390:18–19, 1997. [Online] [PDF].

[83]     K. Sjölander, K. Karplus, M. Brown, R. Hughey, A. Krogh, I.S. Mian, and D. Haussler. Dirichlet mixtures: a method for improving detection of weak but significant protein sequence homology. Comput Appl Biosci, 12:327–345, 1996. [Online] [PDF].

[84]     A. Krogh, M. Brown, I.S. Mian, K. Sjölander, and D. Haussler. Hidden Markov models in computational biology: applications to protein modeling. J Mol Biol, 235:1501–1531, 1994. [Online] [PDF].

[85]     Y. Sakakibara, M. Brown, R.C. Underwood, I.S Mian, and D. Haussler. Stochastic context-free grammars for modeling RNA. In Twenty-Seventh Hawaii Int Conf System Sciences (HICCS), pages 284–293. 1994. [Online] [PDF].

[86]     Y. Sakakibara, M. Brown, R. Hughey, I.S. Mian, K. Sjölander, R. Underwood, and D. Haussler. Recent methods for RNA modeling using stochastic context-free grammars. In Gusfield D. Crochemore M., editor, Combinatorial Pattern Matching (CPM), pages 289–306. 1994. [Online] [PDF].

[87]     Y. Sakakibara, M. Brown, R. Hughey, I.S. Mian, K. Sjölander, R.C. Underwood, and D. Haussler. Stochastic context-free grammars for tRNA modeling. Nucleic Acids Res, 22:5112–5120, 1994. [Online] [PDF].

[88]     L. Grate, M. Herbster, R. Hughey, D. Haussler, I.S. Mian, and H. Noller. RNA modeling using Gibbs sampling and stochastic context free grammars. In Intelligent Systems for Molecular Biology (ISMB), pages 138–146. 1994. [Online] [PDF].

[89]     A. Krogh, I.S. Mian, and D. Haussler. A hidden Markov model that finds genes in E. coli DNA. Nucleic Acids Res, 22:4768–4778, 1994. [Online] [PDF].

[90]     Mian I.S. Sequence similarities between cell regulation factors, heat shock proteins and RNA helicases. Trends Biochem Sci, 18:125–127, 1993. [Online] [PDF].

[91]     Y. Sakikabara, M. Brown, R. Hughey, I.S. Mian, K. Sjölander, R.C. Underwood, and D. Haussler. The application of stochastic context-free grammars to folding, aligning and modeling homologous RNA sequences. Technical report, Department Computer and Information Sciences, University of California Santa Cruz, 1993. [Online] [PDF].

[92]     Y. Sakakibara, M. Brown, R.C. Underwood, I.S. Mian, and D. Haussler. Stochastic context-free grammars in computational biology: applications to modeling RNA. In Genome Informatics Workshop IV (GIW). 1993. [Online] [PDF].

[93]     D. Haussler, A. Krogh, I.S. Mian, and K. Sjölander. Protein modeling using hidden Markov models: analysis of globins. In Twenty-Sixth Hawaii International Conference on System Sciences (HICCS), pages 792–802. 1993. [Online] [PDF].

[94]     M. Brown, R. Hughey, A. Krogh, I.S. Mian, K. Sjölander, and D. Haussler. Using Dirichlet mixture priors to derive hidden Markov models for protein families. In Intelligent Systems for Molecular Biology (ISMB), pages 47–55. 1993. [Online] [PS].

[95]     D.L. Ellenberger, N.J. Pieniazek, I.S. Mian, M.L. Eberhard, and P.J. Lammie. Cloning and characterization of the Wuchereria bancrofti S15 ribosomal protein. Mol Biochem Parasitol, 52:131–135, 1992. [Online] [PDF].

[96]     I.S. Mian, A.R. Bradwell, and A.J. Olson. Structure, function and properties of antibody binding sites. J Mol Biol, 217:133–151, 1991. [Online] [PDF].

[97]     D.S. Goodsell, I.S. Mian, and A.J. Olson. Rendering of volumetric data in molecular systems. J Mol Graph, 7:41–47, 1989. [Online] [PDF].

[98]     I.S. Mian and W.G. Richards. Theoretical binding energies of inhibitors to enzymes. Biochim Biophys Acta, 87:177–179, 1986. [Online] [PDF].