LEADER 03470nam 2200397 450 001 9910476817003321 005 20230511102401.0 035 $a(CKB)5470000000566386 035 $a(NjHacI)995470000000566386 035 $a(EXLCZ)995470000000566386 100 $a20230511d2006 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Changing Landscape of the Academic Profession $ethe culture of faculty at for-profit colleges and universities /$fVicente M. Lechuga 210 1$aNew York :$cTaylor & Francis,$d2006. 215 $a1 online resource (xii, 222 pages) 311 $a1-135-50874-7 327 $aPart I The Changing Landscape of Higher Education; Chapter 1 The Contours of Higher Education; Chapter 2 Mapping the For-Profit Terrain; Chapter 3 A Case Study Approach to Faculty Culture; Part II Perspectives from Within; Chapter 4 Distance Learning University; Chapter 5 Pacific-Atlantic University; Chapter 6 Miller College; Chapter 7 Southeastern College; Chapter 8 Looking Beyond Each Institution; Part III A Distinct Perspective of Faculty Work Life; Chapter 9 A Cross-Institutional Analysis; Chapter 10 Re-Evaluating Faculty Culture Interview Protocol E-mail Invitation. 330 $aThe rapid success of for-profit colleges and universities (FPCUs) only recently has caught the attention of scholars in academe. The continuing expansion of the proprietary higher education sector has lead to fundamental questions regarding the purpose and function of FPCUs. As new technologies continue to emerge, education is becoming of increasing import to employees seeking to upgrade their skills and employers in search of individuals who possess the necessary expertise and training to help their organizations succeed. For-profit institutions challenge traditional notions of the academy--such as shared governance, tenure, and academic freedom--by utilizing administrative practices that more aptly apply to the corporate arena. Moreover, they exclusively employ non-tenure-track faculty members. This study provides a framework for understanding faculty roles and responsibilities at for profit colleges and universities. The author employs a series of in-depth interviews with 53 faculty members, from four for-profit institutions. Utilizing a cultural framework, the study explores the attitudes, beliefs, and perceptions of faculty work with particular consideration given to faculty member's non-tenure-track status, participation in decision-making activities, and academic freedom. The study examines the culture of the faculty work by asking how the profit-seeking nature of the institution affects their efforts inside and outside of the classroom. The author introduces a new component to the cultural framework that illustrates how the close ties between FPCUs and business and industry affect the nature of faculty work. 606 $aCollege teachers$xAttitudes 606 $aFor-profit universities and colleges 606 $aCollege teachers 615 0$aCollege teachers$xAttitudes. 615 0$aFor-profit universities and colleges. 615 0$aCollege teachers. 676 $a378.04 700 $aLechuga$b Vicente M.$0864335 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910476817003321 996 $aThe changing landscape of the academic profession$92937330 997 $aUNINA LEADER 05719nam 2200721Ia 450 001 9910958642403321 005 20251117062842.0 010 $a9781848162525 010 $a1848162529 035 $a(CKB)1000000000767482 035 $a(EBL)1193219 035 $a(SSID)ssj0000519663 035 $a(PQKBManifestationID)12215641 035 $a(PQKBTitleCode)TC0000519663 035 $a(PQKBWorkID)10508618 035 $a(PQKB)10025286 035 $a(MiAaPQ)EBC1193219 035 $a(WSP)00002028 035 $a(Au-PeEL)EBL1193219 035 $a(CaPaEBR)ebr10688048 035 $a(CaONFJC)MIL491649 035 $a(OCoLC)780417054 035 $a(Perlego)845560 035 $a(EXLCZ)991000000000767482 100 $a20090404d2008 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRegulatory genomics $eproceedings of the 3rd annual RECOMB workshop : National University of Singapore, Singapore 17-18 July 2006 /$feditors, Leong Hon Wai, Sung Wing-Kin, Eleazar Eskin 205 $a1st ed. 210 $aLondon $cImperial College Press$dc2008 215 $a1 online resource (144 p.) 225 1 $aSeries on advances in bioinformatics and computational biology,$x1751-6404 ;$v8 300 $aDescription based upon print version of record. 311 08$a9781848162518 311 08$a1848162510 320 $aIncludes bibliographical references and index. 327 $aForeword; RECOMB Regulatory Genomics 2006 Organization; CONTENTS; Keynote Papers; Computational Prediction of Regulatory Elements by Comparative Sequence Analysis M. Tompa; A Tale of Two Topics - Motif Significance and Sensitivity of Spaced Seeds M. Li; Computational Challenges for Top-Down Modeling and Simulation of Biological Pathways S. Miyano; An Improved Gibbs Sampling Method for Motif Discovery via Sequence Weighting T. Jiang; Discovering Motifs with Transcription Factor Domain Knowledge F. Chin; Applications of ILP in Computational Biology A . Dress 327 $aOn the Evolution of Transcription Regulation Networks R. Shamir Systems Pharmacology in Cancer Therapeutics: Iterative Informatics-Experimental Interface E. Liu; Computational Structural Proteomics and Inhibitor Discovery R. Abagyan; Characterization of Transcriptional Responses to Environmental Stress by Differential Location Analysis H. Tang; A Knowledge-based Hybrid Algorithm for Protein Secondary Structure Prediction W. L. Hsu; Monotony and Surprise (Conservative Approaches to Pattern Discovery) A . Apostolic0; Evolution of Bacterial Regulatory Systems M. S. Gelfand; Contributed Papers 327 $aTScan: A Two-step De NOVO Motif Discovery Method 0. Abul, G. K. Sandve, and F. Drabbs1. Introduction; 2. Method; 2.1. Step 1; 2.2. Step 2; 2.2.1, Over-representation Conservation Scoring; 2.2.2. Frith et al. Scoring; 3. Experiments; 4. Conclusion; References; Redundancy Elimination in Motif Discovery Algorithms H. Leung and F. Chin; 1. Introduction; 2. Maximizing Likelihood; 3. The Motif Redundancy Problem; 3.1. The motif redundancy problem; 3.2. Formal definition; 4. Algorithm; 5. Experimental Results; 6. Concluding Remarks; Appendix; References 327 $aGAMOT: An Efficient Genetic Algorithm for Finding Challenging Motifs in DNA Sequences N. Karaoglu, S. Maurer-Stroh, and B. Manderick1. Introduction; 2. GA for Motif Finding; 3. An Efficient Algorithm (GAMOT); 3.1. Fast motif discovery; 3.2. The genetic algorithm; 4. Experimental Results; 4.1. Comparison with exhaustive search; 4.2. Comparison with GAI and GA2; 4.3. Comparison with other algorithms; 4.3.1. Quality of the solutions; 4.4. GAMOTparameters; 5. Conclusions and Future Work; References; Identification of Spaced Regulatory Sites via Submotif Modeling E. Wijaya and R. Kanagasabai 327 $a1. Introduction 2. Related Work; 3. Our Approach; 4. Problem Definition; 5. Algorithm SPACE; 5.1. Generation of candidate motifs; 5.2. Constrained frequent pattern mining; 5.2.1. Generalized gap; 5.2.2. Mining of constrained frequent patterns; 5.3. Significance testing and scoring; 6. Experimental Results; 6.1. Results on Tompa's benchmark data set; 6.2. Results on synthetic data set; 7. Discussion and Conclusions; References; Refining Motif Finders with E-value Calculations N. Nagarajan, P. Ng, and U. Keich; 1. Introduction; 2. Efficiently Computing E-values 327 $a3. Optimizing for E-values - Conspv 330 $aResearch in the field of gene regulation is evolving rapidly in the ever-changing scientific environment. Advances in microarray techniques and comparative genomics have enabled more comprehensive studies of regulatory genomics. The study of genomic binding locations of transcription factors has enabled a more comprehensive modeling of regulatory networks. In addition, complete genomic sequences and comparison of numerous related species have demonstrated the conservation of non-coding DNA sequences, which often provide evidence for cis-regulatory binding sites. Systematic methods to decipher 410 0$aSeries on advances in bioinformatics and computational biology,$x1751-6404 ;$v8. 606 $aGenetic regulation$vCongresses 606 $aGenomics$vCongresses 615 0$aGenetic regulation 615 0$aGenomics 676 $a572.865 701 $aEskin$b Eleazar$01652094 701 $aLeong$b Hon Wai$f1955-$01865910 701 $aSung$b Wing-Kin$01865911 712 12$aRECOMB Satellite Workshop on Regulatory Genomics. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910958642403321 996 $aRegulatory genomics$94473140 997 $aUNINA