Items where Subject is "algorithms"

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Number of items at this level: 123.

A

Aganezov, S., Zban, I., Aksenov, V., Alexeev, N., Schatz, M. C. (December 2019) Recovering rearranged cancer chromosomes from karyotype graphs. BMC Bioinformatics, 20 (Suppl). p. 641. ISSN 1471-2105 (Public Dataset)

B

Ballouz, S., Dobin, A., Gingeras, T. R., Gillis, J. (May 2018) The fractured landscape of RNA-seq alignment: the default in our STARs. Nucleic Acids Res. ISSN 0305-1048

Banerjee, Samik, Magee, Lucas, Wang, Dingkang, Li, Xu, Huo, Bing-Xing, Jayakumar, Jaikishan, Matho, Katherine, Lin, Meng-Kuan, Ram, Keerthi, Sivaprakasam, Mohanasankar, Huang, Josh, Wang, Yusu, Mitra, Partha P (October 2020) Semantic segmentation of microscopic neuroanatomical data by combining topological priors with encoder-decoder deep networks. Nature Machine Intelligence, 2 (10). 585-+. ISSN 2522-5839

Belkin, M., Hsu, D., Mitra, P. P. (December 2018) Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate. In: 32nd Conference on Neural Information Processing Systems, NeurIPS 2018, Montreal, Canada.

Berlow, N. E., Rikhi, R., Geltzeiler, M., Abraham, J., Svalina, M. N., Davis, L. E., Wise, E., Mancini, M., Noujaim, J., Mansoor, A., Quist, M. J., Matlock, K. L., Goros, M. W., Hernandez, B. S., Doung, Y. C., Thway, K., Tsukahara, T., Nishio, J., Huang, E. T., Airhart, S., Bult, C. J., Gandour-Edwards, R., Maki, R. G., Jones, R. L., Michalek, J. E., Milovancev, M., Ghosh, S., Pal, R., Keller, C. (June 2019) Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma. BMC Cancer, 19 (1). p. 593. ISSN 1471-2407 (Public Dataset)

C

Carter, J. A., Gilbo, P., Atwal, G. S. (December 2019) IMPRES does not reproducibly predict response to immune checkpoint blockade therapy in metastatic melanoma. Nat Med, 25 (12). pp. 1833-1835. ISSN 1078-8956 (Public Dataset)

Carter, J. A., Preall, J. B., Atwal, G. S. (October 2019) Bayesian Inference of Allelic Inclusion Rates in the Human T Cell Receptor Repertoire. Cell Syst, 9 (5). pp. 475-482. ISSN 2405-4712 (Public Dataset)

Carter, J. A., Preall, J. B., Grigaityte, K., Goldfless, S. J., Jeffery, E., Briggs, A. W., Vigneault, F., Atwal, G. S. (July 2019) Single T Cell Sequencing Demonstrates the Functional Role alpha beta TCR Pairing in Cell Lineage and Antigen Specificity. Frontiers in Immunology, 10. Article Number:1516. ISSN 1664-3224

Chandrasekhar, A., Gordon, D. M., Navlakha, S. (June 2018) A distributed algorithm to maintain and repair the trail networks of arboreal ants. Sci Rep, 8 (1). p. 9297. ISSN 2045-2322 (Public Dataset)

Chandrasekhar, A., Navlakha, S. (May 2019) Neural arbors are Pareto optimal. Proc Biol Sci, 286 (1902). p. 20182727. ISSN 0962-8452 (Public Dataset)

Chandrasekhar, Arjun, Marshall, James AR, Austin, Cortnea, Navlakha, Saket, Gordon, Deborah M (October 2021) Better tired than lost: Turtle ant trail networks favor coherence over short edges. PLoS Computational Biology, 17 (10). e1009523. ISSN 1553-7358

Chang, W. I., Lampe, J. (1992) Theoretical and Empirical Comparisons of Approximate String Matching Algorithms. Proceedings of the Third Annual Symposium on Combinatorial Pattern Matching, 644. pp. 175-184. ISSN 0302-9743

Chen, S., Krusche, P., Dolzhenko, E., Sherman, R. M., Petrovski, R., Schlesinger, F., Kirsche, M., Bentley, D. R., Schatz, M. C., Sedlazeck, F. J., Eberle, M. A. (December 2019) Paragraph: A graph-based structural variant genotyper for short-read sequence data. Genome Biology, 20 (1). Article 291. ISSN 14747596 (ISSN)

Chen, Y., McElvain, L. E., Tolpygo, A. S., Ferrante, D., Friedman, B., Mitra, P. P., Karten, H. J., Freund, Y., Kleinfeld, D. (March 2019) An active texture-based digital atlas enables automated mapping of structures and markers across brains. Nat Methods, 16 (4). pp. 341-350. ISSN 1548-7091

Chen, Shuonan, Loper, Jackson, Chen, Xiaoyin, Vaughan, Alex, Zador, Anthony M, Paninski, Liam (March 2021) BARcode DEmixing through Non-negative Spatial Regression (BarDensr). PLoS Computational Biology, 17 (3). e1008256. ISSN 1553-734X

Cifani, Paolo, Li, Zhi, Luo, Danmeng, Grivainis, Mark, Intlekofer, Andrew M, Fenyö, David, Kentsis, Alex (April 2021) Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics. Journal of Proteome Research, 20 (4). pp. 1835-1848. ISSN 1535-3893

Cohen, Yarden, Engel, Tatiana A, Langdon, Christopher, Lindsay, Grace W, Ott, Torben, Peters, Megan AK, Shine, James M, Breton-Provencher, Vincent, Ramaswamy, Srikanth (November 2022) Recent Advances at the Interface of Neuroscience and Artificial Neural Networks. The Journal of Neuroscience, 42 (45). pp. 8514-8523. ISSN 1529-2401

Conn, A., Chandrasekhar, A., Rongen, M. V., Leyser, O., Chory, J., Navlakha, S. (September 2019) Network trade-offs and homeostasis in Arabidopsis shoot architectures. PLoS Comput Biol, 15 (9). e1007325. ISSN 1553-734x (Public Dataset)

Czégel, Dániel, Giaffar, Hamza, Tenenbaum, Joshua B, Szathmáry, Eörs (February 2022) Bayes and Darwin: How replicator populations implement Bayesian computations. BioEssays : news and reviews in molecular, cellular and developmental biology. e2100255. ISSN 1521-1878

D

Darby, C.A., Gaddipati, R., Schatz, M.C., Langmead, B. (April 2020) Vargas: Heuristic-Free Alignment for Assessing Linear and Graph Read Aligners. Bioinformatics. ISSN 1367-4803 (Public Dataset)

Das, Arun, Schatz, Michael C (October 2022) Sketching and sampling approaches for fast and accurate long read classification. BMC Bioinformatics, 23 (1). p. 452. ISSN 1471-2105

Dasgupta, S., Sheehan, T. C., Stevens, C. F., Navlakha, S. (December 2018) A neural data structure for novelty detection. Proc Natl Acad Sci U S A, 115 (51). pp. 13093-13098. ISSN 0027-8424 (Public Dataset)

Dasgupta, S., Stevens, C. F., Navlakha, S. (November 2017) A neural algorithm for a fundamental computing problem. Science, 358 (6364). pp. 793-796. ISSN 0036-8075 (Public Dataset)

Derkarabetian, S., Castillo, S., Koo, P. K., Ovchinnikov, S., Hedin, M. (October 2019) A demonstration of unsupervised machine learning in species delimitation. Mol Phylogenet Evol, 139. p. 106562. ISSN 1055-7903

Duggal, Geet, Navlakha, Saket, Girvan, Michelle, Kingsford, Carl (July 2010) Uncovering Many Views of Biological Networks Using Ensembles of Near-Optimal Partitions. MultiClust: 1st International Workshop on Discovering, Summarizing and Using Multiple ClusteringsHeld in Conjunction with KDD-2019.

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Emek, Yuval, Navlakha, Saket (April 2022) Special Issue: Biological Distributed Algorithms 2021. Journal of Computational Biology, 29 (4). p. 305. ISSN 1557-8666

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Fang, Han, Huang, Yi-Fei, Radhakrishnan, Aditya, Siepel, Adam, Lyon, Gholson J., Schatz, Michael C. (February 2018) Scikit-ribo Enables Accurate Estimation and Robust Modeling of Translation Dynamics at Codon Resolution. Cell Systems, 6 (2). pp. 180-191. ISSN 2405-4712

Fischer, Stephan, Gillis, Jesse (October 2022) Defining the extent of gene function using ROC curvature. Bioinformatics. btac692. ISSN 1367-4803

Fleischer, J. G., Schulte, R., Tsai, H. H., Tyagi, S., Ibarra, A., Shokhirev, M. N., Huang, L., Hetzer, M. W., Navlakha, S. (December 2018) Predicting age from the transcriptome of human dermal fibroblasts. Genome Biol, 19 (1). p. 221. ISSN 1474-7596 (Public Dataset)

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Genkin, Mikhail, Hughes, Owen, Engel, Tatiana A (October 2021) Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories. Nature Communications, 12 (1). p. 5986. ISSN 2041-1723

Giovannucci, A., Friedrich, J., Gunn, P., Kalfon, J., Brown, B. L., Koay, S. A., Taxidis, J., Najafi, F., Gauthier, J. L., Zhou, P., Khakh, B. S., Tank, D. W., Chklovskii, D. B., Pnevmatikakis, E. A. (January 2019) CaImAn an open source tool for scalable calcium imaging data analysis. Elife, 8. ISSN 2050-084x

Gomez-Romero, L., Palacios-Flores, K., Reyes, J., Garcia, D., Boege, M., Davila, G., Flores, M., Schatz, M. C., Palacios, R. (May 2018) Precise detection of de novo single nucleotide variants in human genomes. Proc Natl Acad Sci U S A, 115 (21). pp. 5516-5521. ISSN 0027-8424

H

Haas, B. J., Dobin, A., Li, B., Stransky, N., Pochet, N., Regev, A. (October 2019) Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods. Genome Biol, 20 (1). p. 213. ISSN 1474-7596

Hejase, H. A., Dukler, N., Siepel, A. (January 2020) From Summary Statistics to Gene Trees: Methods for Inferring Positive Selection. Trends Genet. ISSN 0168-9525 (Print)0168-9525

Hejase, H. A., Salman-Minkov, A., Campagna, L., Hubisz, M. J., Lovette, I. J., Gronau, I., Siepel, A. (December 2020) Genomic islands of differentiation in a rapid avian radiation have been driven by recent selective sweeps. Proc Natl Acad Sci U S A, 117 (48). pp. 30554-30565. ISSN 0027-8424 (Print)0027-8424

Hejase, Hussein A, Mo, Ziyi, Campagna, Leonardo, Siepel, Adam (November 2021) A Deep-Learning Approach for Inference of Selective Sweeps from the Ancestral Recombination Graph. Molecular Biology and Evolution. ISSN 0737-4038

How, J. J., Navlakha, S. (August 2018) Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks. Neural Comput, 30 (8). pp. 2210-2244. ISSN 0899-7667

How, Javier J, Navlakha, Saket, Chalasani, Sreekanth H (November 2021) Neural network features distinguish chemosensory stimuli in Caenorhabditis elegans. PLoS Computational Biology, 17 (11). e1009591. ISSN 1553-7358

Howe, K. L., Contreras-Moreira, B., De Silva, N., Maslen, G., Akanni, W., Allen, J., Alvarez-Jarreta, J., Barba, M., Bolser, D. M., Cambell, L., Carbajo, M., Chakiachvili, M., Christensen, M., Cummins, C., Cuzick, A., Davis, P., Fexova, S., Gall, A., George, N., Gil, L., Gupta, P., Hammond-Kosack, K. E., Haskell, E., Hunt, S. E., Jaiswal, P., Janacek, S. H., Kersey, P. J., Langridge, N., Maheswari, U., Maurel, T., McDowall, M. D., Moore, B., Muffato, M., Naamati, G., Naithani, S., Olson, A., Papatheodorou, I., Patricio, M., Paulini, M., Pedro, H., Perry, E., Preece, J., Rosello, M., Russell, M., Sitnik, V., Staines, D. M., Stein, J., Tello-Ruiz, M. K., Trevanion, S. J., Urban, M., Wei, S., Ware, D., Williams, G., Yates, A. D., Flicek, P. (January 2020) Ensembl Genomes 2020-enabling non-vertebrate genomic research. Nucleic Acids Res, 48 (1). pp. 689-695. ISSN 0305-1048

Hsieh, T. C., Mensah, M. A., Pantel, J. T., Aguilar, D., Bar, O., Bayat, A., Becerra-Solano, L., Bentzen, H. B., Biskup, S., Borisov, O., Braaten, O., Ciaccio, C., Coutelier, M., Cremer, K., Danyel, M., Daschkey, S., Eden, H. D., Devriendt, K., Wilson, S., Douzgou, S., Dukic, D., Ehmke, N., Fauth, C., Fischer-Zirnsak, B., Fleischer, N., Gabriel, H., Graul-Neumann, L., Gripp, K. W., Gurovich, Y., Gusina, A., Haddad, N., Hajjir, N., Hanani, Y., Hertzberg, J., Hoertnagel, K., Howell, J., Ivanovski, I., Kaindl, A., Kamphans, T., Kamphausen, S., Karimov, C., Kathom, H., Keryan, A., Knaus, A., Kohler, S., Kornak, U., Lavrov, A., Leitheiser, M., Lyon, G. J., Mangold, E., Reina, P. M., Carrascal, A. M., Mitter, D., Herrador, L. M., Nadav, G., Nothen, M., Orrico, A., Ott, C. E., Park, K., Peterlin, B., Polsler, L., Raas-Rothschild, A., Randolph, L., Revencu, N., Fagerberg, C. R., Robinson, P. N., Rosnev, S., Rudnik, S., Rudolf, G., Schatz, U., Schossig, A., Schubach, M., Shanoon, O., Sheridan, E., Smirin-Yosef, P., Spielmann, M., Suk, E. K., Sznajer, Y., Thiel, C. T., Thiel, G., Verloes, A., Vrecar, I., Wahl, D., Weber, I., Winter, K., Wisniewska, M., Wollnik, B., Yeung, M. W., Zhao, M., Zhu, N., Zschocke, J., Mundlos, S., Horn, D., Krawitz, P. M. (June 2019) PEDIA: prioritization of exome data by image analysis. Genet Med, 21 (12). pp. 2807-2814. ISSN 1098-3600

Hu, Haifei, Scheben, Armin, Wang, Jian, Li, Fangping, Li, Chengdao, Edwards, David, Zhao, Junliang (November 2023) Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding. Plant Biotechnology Journal. ISSN 1467-7644

Huang, Yi-Fei, Siepel, Adam (June 2019) Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease. Genome Research, 29 (8). pp. 1310-1321. ISSN 10889051 (ISSN)

Hubisz, M., Siepel, A. (January 2020) Inference of Ancestral Recombination Graphs Using ARGweaver. Methods Mol Biol, 2090. pp. 231-266. ISSN 1064-3745

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Kaczmarzyk, Jakub R, Gupta, Rajarsi, Kurc, Tahsin M, Abousamra, Shahira, Saltz, Joel H, Koo, Peter K (September 2023) ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification. Computer Methods and Programs in Biomedicine, 239. p. 107631. ISSN 0169-2607

Kawaguchi, Risa K., Takahashi, Masamichi, Miyake, Mototaka, Kinoshita, Manabu, Takahashi, Satoshi, Ichimura, Koichi, Hamamoto, Ryuji, Narita, Yoshitaka, Sese, Jun (July 2021) Assessing Versatile Machine Learning Models for Glioma Radiogenomic Studies across Hospitals. Cancers, 13 (14). p. 3611. ISSN 2072-6694

Kepple, D. R., Giaffar, H., Rinberg, D., Koulakov, A. A. (February 2019) Deconstructing Odorant Identity via Primacy in Dual Networks. Neural Computation, 31 (4). pp. 710-737. ISSN 08997667 (ISSN)

Kirsche, Melanie, Das, Arun, Schatz, Michael C (May 2021) Sapling: accelerating suffix array queries with learned data models. Bioinformatics, 37 (6). pp. 744-749. ISSN 1367-4803

Kiyani, E, Silber, S, Kooshkbaghi, M, Karttunen, M (December 2022) Machine-learning-based data-driven discovery of nonlinear phase-field dynamics. Physical Review E, 106 (6). ISSN 2470-0045

Klindt, David (December 2022) Controlling neural network smoothness for neural algorithmic reasoning. Transactions on Machine Learning Research.

Klindt, David, Sanborn, Sophia, Acosta, Francisco, Poitevin, Frédéric, Miolane, Nina (October 2023) Identifying Interpretable Visual Features in Artificial and Biological Neural Systems. arXiv. (Submitted)

Klindt, David A, Hyvärinen, Aapo, Levy, Axel, Miolane, Nina, Poitevin, Frédéric (March 2024) Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations. bioRxiv. (Submitted)

Koo, PK, Ploenzke, M (February 2020) Deep learning for inferring transcription factor binding sites. Current Opinion in Systems Biology, 19. pp. 16-23. ISSN 2452-3100

Koo, Peter K, Majdandzic, Antonio, Ploenzke, Matthew, Anand, Praveen, Paul, Steffan B (May 2021) Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks. PLoS Computational Biology, 17 (5). e1008925. ISSN 1553-7358

Koo, Peter K, Ploenzke, Matt (March 2021) Improving representations of genomic sequence motifs in convolutional networks with exponential activations. Nature Machine Intelligence, 3 (3). pp. 258-266. ISSN 2522-5839

Kovaka, Sam, Fan, Yunfan, Ni, Bohan, Timp, Winston, Schatz, Michael C (April 2021) Targeted nanopore sequencing by real-time mapping of raw electrical signal with UNCALLED. Nature Biotechnology, 39 (4). pp. 431-441. ISSN 1087-0156

Krauthammer, M., Kra, P., Iossifov, I., Gomez, S. M., Hripcsak, G., Hatzivassiloglou, V., Friedman, C., Rzhetsky, A. (2002) Of truth and pathways: chasing bits of information through myriads of articles. Bioinformatics, 18 Sup. S249-57. ISSN 1367-4803 (Print)1367-4803 (Linking)

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Li, Siran, Park, Sarah, Ye, Catherine, Danyko, Cassidy, Wroten, Matthew, Andrews, Peter, Wigler, Michael, Levy, Dan (July 2022) Targeted de novo phasing and long-range assembly by template mutagenesis. Nucleic Acids Research. ISSN 0305-1048

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Macpherson, Tom, Churchland, Anne, Sejnowski, Terry, DiCarlo, James, Kamitani, Yukiyasu, Takahashi, Hidehiko, Hikida, Takatoshi (September 2021) Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research. Neural Networks. ISSN 0893-6080

Majdandzic, Antonio, Koo, Peter K (May 2022) Statistical correction of input gradients for black box models trained with categorical input features. BioRxiv. (Unpublished)

Marr, T. G., Yan, X., Yu, Q. (1992) Genomic mapping by single copy landmark detection: a predictive model with a discrete mathematical approach. Mamm Genome, 3 (11). pp. 644-9. ISSN 0938-8990 (Print)0938-8990 (Linking)

Mitra, Partha P, Sire, Clément (December 2023) AI without networks. bioRxiv. (Submitted)

Mitra, P. P. (November 2018) Fast convergence for stochastic and distributed gradient descent in the interpolation limit. European Signal Processing Conference, EUSIPCO, pp. 1890-1894. ISBN 22195491 (ISSN); 9789082797015 (ISBN)

Mo, Ziyi, Siepel, Adam (November 2023) Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data. PLoS Genetics, 19 (11). e1011032. ISSN 1553-7390

Moffitt, A. B., Spector, M. S., Andrews, P., Kendall, J., Alexander, J., Stepansky, A., Ma, B., Kolitz, J., Chiorazzi, N., Allen, S.L., Krasnitz, A., Wigler, M., Levy, D., Wang, Z. (February 2020) Multiplex Accurate Sensitive Quantitation (MASQ) With Application to Minimal Residual Disease in Acute Myeloid Leukemia. Nucleic Acids Research, 48 (7). e40. ISSN 0305-1048 (Public Dataset)

Molik, David C, Tomlinson, DeAndre, Davitt, Shane, Morgan, Eric L, Sisk, Matthew, Roche, Benjamin, Meyers, Natalie, Pfrender, Michael E (April 2021) Combining natural language processing and metabarcoding to reveal pathogen-environment associations. PLoS Neglected Tropical Diseases, 15 (4). e0008755. ISSN 1935-2735

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Navlakha, S., Ahammad, P., Myers, E. W. (October 2013) Unsupervised segmentation of noisy electron microscopy images using salient watersheds and region merging. BMC Bioinformatics, 14. p. 294. ISSN 1471-2105

Navlakha, S., Bar-Joseph, Z. (November 2011) Algorithms in nature: the convergence of systems biology and computational thinking. Mol Syst Biol, 7. p. 546. ISSN 1744-4292

Navlakha, S., Bar-Joseph, Z. (January 2015) Distributed information processing in biological and computational systems. Communications of the ACM, 58 (1). pp. 94-102. ISSN 00010782 (ISSN)

Navlakha, S., Bar-Joseph, Z., Barth, A. L. (January 2018) Network Design and the Brain. Trends Cogn Sci, 22 (1). pp. 64-78. ISSN 1364-6613

Navlakha, S., Barth, A. L., Bar-Joseph, Z. (July 2015) Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks. PLoS Comput Biol, 11 (7). e1004347. ISSN 1553-734x

Navlakha, S., Faloutsos, C., Bar-Joseph, Z. (September 2015) MassExodus: modeling evolving networks in harsh environments. Data Mining and Knowledge Discovery, 29 (5). pp. 1211-1232. ISSN 13845810 (ISSN)

Navlakha, S., Gitter, A., Bar-Joseph, Z. (August 2012) A network-based approach for predicting missing pathway interactions. PLoS Comput Biol, 8 (8). e1002640. ISSN 1553-734x

Navlakha, S., He, X., Faloutsos, C., Bar-Joseph, Z. (July 2014) Topological properties of robust biological and computational networks. J R Soc Interface, 11 (96). p. 20140283. ISSN 1742-5662

Navlakha, S., Kingsford, C. (November 2010) Exploring biological network dynamics with ensembles of graph partitions. Pac Symp Biocomput. pp. 166-177. ISSN 2335-6928

Navlakha, S., Kingsford, C. (April 2011) Network archaeology: uncovering ancient networks from present-day interactions. PLoS Comput Biol, 7 (4). e1001119. ISSN 1553-734x (Public Dataset)

Navlakha, S., Kingsford, C. (April 2010) The power of protein interaction networks for associating genes with diseases. Bioinformatics, 26 (8). pp. 1057-63. ISSN 1367-4803 (Public Dataset)

Navlakha, S., Rastogi, R., Shrivastava, N. (June 2008) Graph summarization with bounded error. ACM, 419-431; Art no. 1376661. ISBN 07308078 (ISSN); 9781605581026 (ISBN)

Navlakha, S., Schatz, M. C., Kingsford, C. (February 2009) Revealing biological modules via graph summarization. J Comput Biol, 16 (2). pp. 253-64. ISSN 1066-5277

Navlakha, S., White, J., Nagarajan, N., Pop, M., Kingsford, C. (May 2009) Finding biologically accurate clusterings in hierarchical tree decompositions using the variation of information. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5541 L . Springer, pp. 400-417. ISBN 03029743 (ISSN); 9783642020070 (ISBN)

Navlakha, Saket, Morjaria, Sejal, Perez-Johnston, Rocio, Zhang, Allen, Taur, Ying (May 2021) Projecting COVID-19 disease severity in cancer patients using purposefully-designed machine learning. BMC Infectious Diseases, 21 (1). p. 391. ISSN 1471-2334

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Ou, S., Su, W., Liao, Y., Chougule, K., Agda, J. R. A., Hellinga, A. J., Lugo, C. S. B., Elliott, T. A., Ware, D., Peterson, T., Jiang, N., Hirsch, C. N., Hufford, M. B. (December 2019) Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline. Genome Biol, 20 (1). p. 275. ISSN 1474-7596 (Public Dataset)

O’Neill, Kathryn Shea (June 2022) Investigations into the contribution of retrotransposon activation in neurodegenerative disease. PhD thesis, Cold Spring Harbor Laboratory.

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Patel, H, Zanos, T, Hewitt, DB (January 2024) Deep Learning Applications in Pancreatic Cancer. Cancers, 16 (2). p. 436. ISSN 2072-6694

Patro, R., Sefer, E., Malin, J., Marçais, G., Navlakha, S., Kingsford, C. (September 2012) Parsimonious reconstruction of network evolution. Algorithms for Molecular Biology, 7 (25). (Public Dataset)

Petti, Samantha, Bhattacharya, Nicholas, Rao, Roshan, Dauparas, Justas, Thomas, Neil, Zhou, Juannan, Rush, Alexander M, Koo, Peter, Ovchinnikov, Sergey (November 2022) End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman. Bioinformatics. ISSN 1367-4803

Phan, Minh Son, Matho, Katherine, Beaurepaire, Emmanuel, Livet, Jean, Chessel, Anatole (July 2022) nAdder: A scale-space approach for the 3D analysis of neuronal traces. PLoS Computational Biology, 18 (7). e1010211. ISSN 1553-734X

Pollatou, A., Ferrante, D. D. (August 2020) Out-of-focus brain image detection in serial tissue sections. J Neurosci Methods, 345. p. 108852. ISSN 0165-0270

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Ranallo-Benavidez, T.R., Jaron, K.S., Schatz, M. C. (March 2020) GenomeScope 2.0 and Smudgeplot for Reference-Free Profiling of Polyploid Genomes. Nat Commun, 11 (1432). pp. 1-10. ISSN 2041-1723 (Public Dataset)

Rashid, Sabrina, Singh, Shashank, Navlakha, Saket, Bar-Joseph, Ziv (May 2019) A bacterial based distributed gradient descent model for mass scale evacuations. Swarm and Evolutionary Computation, 46. pp. 97-103. ISSN 2210-6502

Redish, A David, Kepecs, Adam, Anderson, Lisa M, Calvin, Olivia L, Grissom, Nicola M, Haynos, Ann F, Heilbronner, Sarah R, Herman, Alexander B, Jacob, Suma, Ma, Sisi, Vilares, Iris, Vinogradov, Sophia, Walters, Cody J, Widge, Alik S, Zick, Jennifer L, Zilverstand, Anna (February 2022) Computational validity: using computation to translate behaviours across species. Philosophical Transactions of the Royal Society B: Biological Sciences, 377 (1844). p. 20200525. ISSN 0962-8436

Richards, B. A., Lillicrap, T. P., Beaudoin, P., Bengio, Y., Bogacz, R., Christensen, A., Clopath, C., Costa, R. P., de Berker, A., Ganguli, S., Gillon, C. J., Hafner, D., Kepecs, A., Kriegeskorte, N., Latham, P., Lindsay, G. W., Miller, K. D., Naud, R., Pack, C. C., Poirazi, P., Roelfsema, P., Sacramento, J., Saxe, A., Scellier, B., Schapiro, A. C., Senn, W., Wayne, G., Yamins, D., Zenke, F., Zylberberg, J., Therien, D., Kording, K. P. (November 2019) A deep learning framework for neuroscience. Nat Neurosci, 22 (11). pp. 1761-1770. ISSN 1097-6256

Richards, Blake, Tsao, Doris, Zador, Anthony (July 2022) The application of artificial intelligence to biology and neuroscience. Cell, 185 (15). pp. 2640-2643. ISSN 0092-8674

Rodriguez-Esteban, R., Iossifov, I., Rzhetsky, A. (September 2006) Imitating manual curation of text-mined facts in biomedicine. PLoS Comput Biol, 2 (9). e118. ISSN 1553-7358 (Electronic)1553-734X (Linking)

Roux de Bézieux, Hector, Street, Kelly, Fischer, Stephan, Van den Berge, Koen, Chance, Rebecca, Risso, Davide, Gillis, Jesse, Ngai, John, Purdom, Elizabeth, Dudoit, Sandrine (May 2024) Improving replicability in single-cell RNA-Seq cell type discovery with Dune. BMC Bioinformatics, 25 (1). p. 198. ISSN 1471-2105 (Public Dataset)

Rzhetsky, A., Iossifov, I., Loh, J. M., White, K. P. (March 2006) Microparadigms: chains of collective reasoning in publications about molecular interactions. Proceedings of the National Academy of Sciences of the United States of America, 103 (13). pp. 4940-5. ISSN 0027-8424

S

Saxena, S., Kinsella, I., Musall, S., Kim, S.H., Meszaros, J., Thibodeaux, D.N., Kim, C., Cunningham, J., Hillman, E.M.C., Churchland, A., Paninski, L. (April 2020) Localized Semi-Nonnegative Matrix Factorization (LocaNMF) of Widefield Calcium Imaging Data. PLoS Comput Biol, 16 (4). e1007791. ISSN 1553-734x

Shahri, H. H., Namata, G., Navlakha, S., Deshpande, A., Roussopoulos, N. (September 2007) A graph-based approach to vehicle tracking in traffic camera video streams. Proceedings of the 4th workshop on Data management for sensor networks: in conjunction with 33rd International Conference on Very Large Data Bases , 273 . ACM International Conference Proceeding Series, pp. 19-24. ISBN 9781595939111 (ISBN)

Sharma, Ashika, Jayakumar, Jaikishan, Mitra, Partha P, Chakraborti, Sutanu, Kumar, P Sreenivasa (June 2021) Application of Supervised Machine Learning to Extract Brain Connectivity Information from Neuroscience Research Articles. Interdisciplinary Sciences: Computational Life Sciences. ISSN 1913-2751

Shen, Yang, Dasgupta, Sanjoy, Navlakha, Saket (September 2023) Reducing Catastrophic Forgetting With Associative Learning: A Lesson From Fruit Flies. Neural Computation. pp. 1-23. ISSN 0899-7667

Shen, Y., Dasgupta, S., Navlakha, S. (May 2020) Habituation as a Neural Algorithm for Online Odor Discrimination. Proceedings of the National Academy of Sciences of the United States of America, 117 (22). pp. 12402-12410. ISSN 0027-8424

Shen, Y., Dasgupta, S., Navlakha, S. (August 2020) Reply to Semelidou and Skoulakis: "Short-term" habituation has multiple distinct mechanisms. Proc Natl Acad Sci U S A, 117 (34). pp. 20373-20374. ISSN 0027-8424

Shen, Yang, Wang, Julia, Navlakha, Saket (August 2021) A Correspondence between Normalization Strategies in Artificial and Biological Neural Networks. Neural Computation. pp. 1-25. ISSN 0899-7667

Shuvaev, Sergey, Lazutkin, Alexander, Kiryanov, Roman, Anokhin, Konstantin, Enikolopov, Grigori, Koulakov, Alexei A (March 2022) Spatiotemporal 3D image registration for mesoscale studies of brain development. Scientific Reports, 12 (1). p. 3648. ISSN 2045-2322

Shuvaev, Sergey A, Tran, Ngoc B, Stephenson-Jones, Marcus, Li, Bo, Koulakov, Alexei A (January 2021) Neural Networks With Motivation. Frontiers in Systems Neuroscience, 14. p. 609316. ISSN 1662-5137

Silva, Talita M, Borniger, Jeremy C, Alves, Michele Joana, Alzate Correa, Diego, Zhao, Jing, Fadda, Paolo, Toland, Amanda Ewart, Takakura, Ana C, Moreira, Thiago S, Czeisler, Catherine M, Otero, José Javier (April 2021) Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice. Journal of Neurophysiology, 125 (4). pp. 1164-1179. ISSN 0022-3077

Sindhwani, S., Syed, A.M., Ngai, J., Kingston, B.R., Maiorino, L., Rothschild, J., MacMillan, P., Zhang, Y., Rajesh, N.U., Hoang, T., Wu, J.L.Y., Wilhelm, S., Zilman, A., Gadde, S., Sulaiman, A., Ouyang, B., Lin, Z., Wang, L., Egeblad, M., Chan, W.C.W. (January 2020) The entry of nanoparticles into solid tumours. Nat Mater. ISSN 1476-1122 (Public Dataset)

Singh, Shashank, Rashid, Sabrina, Long, Zhicheng, Navlakha, Saket, Salman, Hanna, Oltvai, Zoltan, Bar-Joseph, Ziv (April 2016) Distributed Gradient Descent in Bacterial Food Search. Research in Computational Molecular Biology, 9649. ISSN 978-3-319-31957-5

Suen, J. Y., Navlakha, S. (May 2019) Travel in city road networks follows similar transport trade-off principles to neural and plant arbors. J R Soc Interface, 16 (154). p. 20190041. ISSN 1742-5662 (Public Dataset)

Suen, Jonathan Y, Navlakha, Saket (March 2022) A feedback control principle common to several biological and engineered systems. Journal of the Royal Society Interface, 19 (188). p. 20210711. ISSN 1742-5662

Sun, Shenghuan, Torok, Justin, Mezias, Christopher, Ma, Daren, Raj, Ashish (October 2023) Spatial cell-type enrichment predicts mouse brain connectivity. Cell Reports, 42 (10). p. 113258. ISSN 2211-1247

T

Tello-Ruiz, M. K., Marco, C. F., Hsu, F. M., Khangura, R. S., Qiao, P., Sapkota, S., Stitzer, M. C., Wasikowski, R., Wu, H., Zhan, J., Chougule, K., Barone, L. C., Ghiban, C., Muna, D., Olson, A. C., Wang, L., Ware, D., Micklos, D. A. (October 2019) Double triage to identify poorly annotated genes in maize: The missing link in community curation. PLoS ONE, 14 (10). Article number e0224086. ISSN 19326203 (ISSN)

Thor, A., Anderson, P., Raschid, L., Navlakha, S., Saha, B., Khuller, S., Zhang, X. N. (October 2011) Link prediction for annotation graphs using graph summarization. Lecture Notes in Computer Science, 7031 L (Part 1). Springer, pp. 714-729. ISBN 03029743 (ISSN); 9783642250729 (ISBN)

Toneyan, Shushan, Tang, Ziqi, Koo, Peter K (December 2022) Evaluating deep learning for predicting epigenomic profiles. Nature Machine Intelligence, 4 (12). pp. 1088-1100. ISSN 2522-5839

W

Wang, Julia H, Tsin, Dexter, Engel, Tatiana A (December 2023) Predictive variational autoencoder for learning robust representations of time-series data. arXiv. (Submitted)

Wang, J. T. L., Marr, T. G., Shasha, D., Shapiro, B. A., Chirn, G. W. (July 1994) Discovering Active Motifs in Sets of Related Protein Sequences and Using Them for Classification. Nucleic Acids Research, 22 (14). pp. 2769-2775. ISSN 0305-1048

Weinstein, Jonathan Yaacov, Martí-Gómez, Carlos, Lipsh-Sokolik, Rosalie, Hoch, Shlomo Yakir, Liebermann, Demian, Nevo, Reinat, Weissman, Haim, Petrovich-Kopitman, Ekaterina, Margulies, David, Ivankov, Dmitry, McCandlish, David M, Fleishman, Sarel J (May 2023) Designed active-site library reveals thousands of functional GFP variants. Nature Communications, 14 (1). p. 2890. ISSN 2041-1723

Y

Yu, Yiyang, Muthukumar, Shivani, Koo, Peter K (January 2024) EvoAug-TF: Extending evolution-inspired data augmentations for genomic deep learning to TensorFlow. bioRxiv. (Submitted)

Yu, Yiyang, Muthukumar, Shivani, Koo, Peter K (February 2024) EvoAug-TF: Extending evolution-inspired data augmentations for genomic deep learning to TensorFlow. Bioinformatics. ISSN 1367-4811

Z

Zador, A. M. (August 2019) A critique of pure learning and what artificial neural networks can learn from animal brains. Nat Commun, 10 (1). p. 3770. ISSN 2041-1723

Zaki, A., Mitra, P. P., Rasmussen, L. K., Chatterjee, S. (March 2019) Estimate exchange over network is good for distributed hard thresholding pursuit. Signal Processing, 156. pp. 1-11. ISSN 01651684 (ISSN)

Zhu, Jiening, Oh, Jung Hun, Simhal, Anish K, Elkin, Rena, Norton, Larry, Deasy, Joseph O, Tannenbaum, Allen (September 2023) Geometric graph neural networks on multi-omics data to predict cancer survival outcomes. Computers in Biology and Medicine, 163. p. 107117. ISSN 0010-4825

Ziamtsov, I., Navlakha, S. (October 2019) Machine learning approaches to improve three basic plant phenotyping tasks using 3D point clouds. Plant Physiol. ISSN 0032-0889

Ziamtsov, I., Navlakha, S. (March 2020) Plant 3D (P3D): A Plant Phenotyping Toolkit for 3D Point Clouds. Bioinformatics. ISSN 1367-4803 (Public Dataset)

This list was generated on Thu Jul 18 22:19:07 2024 EDT.
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