Item card
Bioinformatics in diagnostics
Some basic information about the module
Cycle of education:
2022/2023
The name of the faculty organization unit:
The faculty Chemistry
The name of the field of study:
Biotechnology
The area of study:
technical sciences
The profile of studing:
The level of study:
second degree study
Type of study:
full time
discipline specialities :
Laboratory diagnostics in biotechnology, Pharmaceutical biotechnology, Process and bioprocess engineering, Purification and analysis of biotechnological products
The degree after graduating from university:
Master of Science (MSc)
The name of the module department :
Department of Biochemistry and Bioinformatics
The code of the module:
10254
The module status:
mandatory for the speciality Laboratory diagnostics in biotechnology
The position in the studies teaching programme:
sem: 2 / W15 L15 / 2 ECTS / Z
The language of the lecture:
Polish
The name of the coordinator 1:
Andrzej Łyskowski, PhD, Eng.
office hours of the coordinator:
Konsultacje w trybie zdalnym po wcześniejszym zgłoszeniu:
Poniedziałek: 12:15 - 13:45;
Czwartek: 12:15 - 13:45.
The name of the coordinator 2:
Grzegorz Fic, PhD, Eng.
office hours of the coordinator:
wtorki, 19-20.30 online MS Teams, e-mail gfic@prz.edu.pl - zawsze
semester 2:
Marcin Jaromin, MSc, Eng.
The aim of studying and bibliography
The main aim of study:
Gaining knowledge and skills in computer-aided research in pharmacy
The general information about the module:
The module is realized in the form of lectures (15 h) and problem exercises in computer laboratory (15 h)
Teaching materials:
Materiały dydaktyczne dostepne on-line w portalu http://e-learning.prz.edu.pl/.
Bibliography required to complete the module
| 1 | A. D. Baxevanis, B. F. F. Ouellette | Bioinformatyka . Podręcznik do analizy genów i białek | PWN Warszawa. | 2004 |
| 2 | P. G. Higgs, T. K. Attwood | Bioinformatyka i ewolucja molekularna | PWN Warszawa. | 2008 |
| 3 | J.Xiong | Podstawy bioinformatyki | Wydawnictwa Uniwersytetu Warszawskiego. | 2009 |
| 1 | Materiały dydaktyczne dostepne on-line w portalu http://e-learning.prz.edu.pl/. | - | -. | - |
Basic requirements in category knowledge/skills/social competences
Formal requirements:
Registration for the current semester.
Basic requirements in category knowledge:
Basic knowledge of organic chemistry, molecular biology, computer usage.
Basic requirements in category skills:
Computer skills - Windows.
Basic requirements in category social competences:
Ability to work individually and in a team of 2-3 persons.
Module outcomes
| MEK | The student who completed the module | Types of classes / teaching methods leading to achieving a given outcome of teaching | Methods of verifying every mentioned outcome of teaching | Relationships with KEK | Relationships with PRK |
|---|---|---|---|---|---|
| MEK01 | Can use and modify parameters od dedicated computer programs to solve simple problems in molecular biology and biotechnology | lecture, laboratory | test, observation of the task performance, project report, |
K-W02++ K-U07++ K-K02+ |
P7S-KR P7S-UW P7S-WG |
| MEK02 | Knows the basics of biological information processing using computer systems. | lecture, laboratory | written exam, test, observation of the task performance, project report |
K-W02++ K-U07++ |
P7S-UW P7S-WG |
| MEK03 | Is able to use specialized computer programs for searching and for analysis of biological information. | laboratory | test, observation of the task performance, project report |
K-W02++ K-U07++ |
P7S-UW P7S-WG |
| MEK04 | Can use the selected artificial intelligence methods to support engineering tasks and scientific research in the field of molecular biology and biotechnology | lecture, laboratory | test, written report |
K-W02+++ K-U07++ |
P7S-UW P7S-WG |
The syllabus of the module
| Sem. | TK | The content | realized in | MEK |
|---|---|---|---|---|
| 2 | TK01 | W01 | MEK04 | |
| 2 | TK02 | W02 | MEK04 | |
| 2 | TK03 | W03 | MEK03 MEK04 | |
| 2 | TK04 | W06 | MEK01 | |
| 2 | TK05 | L01 | MEK03 | |
| 2 | TK06 | L02 | MEK02 | |
| 2 | TK07 | W07 | MEK04 |
The student's effort
| The type of classes | The work before classes | The participation in classes | The work after classes |
|---|---|---|---|
| Lecture (sem. 2) | The preparation for a test:
5.00 hours/sem. |
contact hours:
15.00 hours/sem. |
Studying the recommended bibliography:
2.00 hours/sem. |
| Laboratory (sem. 2) | The preparation for a Laboratory:
5.00 hours/sem. The preparation for a test: 10.00 hours/sem. |
contact hours:
15.00 hours/sem. |
Finishing/Making the report:
5.00 hours/sem. |
| Advice (sem. 2) | |||
| Credit (sem. 2) |
The way of giving the component module grades and the final grade
| The type of classes | The way of giving the final grade |
|---|---|
| Lecture | The pass note is granted to students with at least 50% of points from the written test. |
| Laboratory | Credit is granted for to the students who participated in all exercises, passed all control tests and submitted all required reports. |
| The final grade | The final note is an derivaticve of all points/partial notes collected from the module activities and precise rages are communicated before the test. The final note is calculated according to equation: K=a*wA+c*wC+l*wL (a-lecture coeff., c-tutorial coeff., l-laboratory/project coeff., w=1,0, w=0,9, w=0,8 receptively for the 1st, 2nd, 3rd attempt). The note is calculated only if all components have been passed. Values of coefficiants are presented to the students during the initial teaching session. |
Sample problems
Required during the exam/when receiving the credit
(-)
Realized during classes/laboratories/projects
(-)
Others
(-)
Can a student use any teaching aids during the exam/when receiving the credit : no
The contents of the module are associated with the research profile yes
| 1 | A. Bocian; A. Łyskowski; B. Marczak | Antimicrobial Peptide Databases as the Guiding Resource in New Antimicrobial Agent Identification via Computational Methods | 2025 |
| 2 | A. Bocian; J. Buczkowicz; E. Ciszkowicz; K. Hus; K. Lecka-Szlachta; A. Łyskowski | Peptyd antybakteryjny oraz jego zastosowanie | 2025 |
| 3 | A. Bocian; J. Buczkowicz; E. Ciszkowicz; K. Hus; K. Lecka-Szlachta; A. Łyskowski | Peptyd antybakteryjny oraz zastosowanie tego peptydu antybakteryjnego | 2025 |
| 4 | E. Ciszkowicz; M. Dżugan; A. Łyskowski; M. Miłek; M. Tomczyk | Selected Polyphenols of Polish Poplar Propolis as a Key Component Shaping Its Antibacterial Properties—In Vitro and In Silico Approaches | 2025 |
| 5 | M. Bauer; A. Bocian; J. Buczkowicz; E. Ciszkowicz; K. Hus; W. Kamysz; K. Lecka-Szlachta; A. Łyskowski; A. Miłoś; D. Neubauer; A. Nieczaj; K. Sikora | AMPEC4: Naja ashei Venom-Derived Peptide as a Stimulator of Fibroblast Migration with Antibacterial Activity | 2025 |
| 6 | M. Dąbrowska; A. Łyskowski; M. Misiorek; Ż. Szymaszek; M. Twardowska; Ł. Uram; S. Wołowiec | Human Embryonic Kidney HEK293 Cells as a Model to Study SMVT-Independent Transport of Biotin and Biotin-Furnished Nanoparticles in Targeted Therapy | 2025 |
| 7 | A. Łyskowski; M. Misiorek; Z. Rauk; Z. Setkowicz; Ż. Szymaszek; M. Twardowska; Ł. Uram; S. Wołowiec | The Importance of Biotinylation for the Suitability of Cationic and Neutral Fourth-Generation Polyamidoamine Dendrimers as Targeted Drug Carriers in the Therapy of Glioma and Liver Cancer | 2024 |
| 8 | M. Dżugan; A. Łyskowski; M. Miłek | Assessing the Antimicrobial Properties of Honey Protein Components through In Silico Comparative Peptide Composition and Distribution Analysis | 2023 |
| 9 | V. Csitkovits; K. Gruber; C. Kratky; B. Kräutler; A. Łyskowski | Structure-Based Demystification of Radical Catalysis by a Coenzyme B12 dependent Enzyme – Crystallographic Study of Glutamate Mutase with Cofactor Homologues | 2022 |
| 10 | J. Buczkowicz; T. Drzazga; G. Fic; M. Jaromin; P. Krajewski; P. Matysik; R. Mazur; P. Milczarski; T. Sikora; M. Szeliga; D. Tyrka; M. Tyrka; E. Witkowski | Selekcja genomowa pszenicy ozimej | 2021 |
| 11 | K. Chen; Ł. Jaremko; M. Jaremko; A. Łyskowski | Genetic and Molecular Factors Determining Grain Weight in Rice | 2021 |